I'm having an issue trying to get this working on my own pc.
GoddessFreya13 opened this issue · 2 comments
This is the error code that keeps showing up once I try to generate an image with the prompt for the apple in a fruit bowl.
(VQGAN+CLIP-AI-Art-Generation-Repository-NerdyRodent) D:\VQGAN+CLIP AI Art Generation Repository - NerdyRodent\VQGAN-CLIP>python generate.py -p "A painting of an apple in a fruit bowl"
Working with z of shape (1, 256, 16, 16) = 65536 dimensions.
loaded pretrained LPIPS loss from taming/modules/autoencoder/lpips\vgg.pth
VQLPIPSWithDiscriminator running with hinge loss.
Traceback (most recent call last):
File "D:\VQGAN+CLIP AI Art Generation Repository - NerdyRodent\VQGAN-CLIP\generate.py", line 546, in
model = load_vqgan_model(args.vqgan_config, args.vqgan_checkpoint).to(device)
File "D:\VQGAN+CLIP AI Art Generation Repository - NerdyRodent\VQGAN-CLIP\generate.py", line 520, in load_vqgan_model
model.init_from_ckpt(checkpoint_path)
File "D:\VQGAN+CLIP AI Art Generation Repository - NerdyRodent\VQGAN-CLIP\taming-transformers\taming\models\vqgan.py", line 52, in init_from_ckpt
self.load_state_dict(sd, strict=False)
File "D:\Anaconda\envs\VQGAN+CLIP-AI-Art-Generation-Repository-NerdyRodent\lib\site-packages\torch\nn\modules\module.py", line 1406, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for VQModel:
size mismatch for encoder.down.1.block.0.conv1.weight: copying a param with shape torch.Size([256, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for encoder.down.1.block.0.conv1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.0.norm2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.0.norm2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.0.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for encoder.down.1.block.0.conv2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.1.norm1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.1.norm1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.1.conv1.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for encoder.down.1.block.1.conv1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.1.norm2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.1.norm2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.block.1.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for encoder.down.1.block.1.conv2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.1.downsample.conv.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for encoder.down.1.downsample.conv.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.2.block.0.norm1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.2.block.0.norm1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for encoder.down.2.block.0.conv1.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 128, 3, 3]).
size mismatch for encoder.down.3.block.0.conv1.weight: copying a param with shape torch.Size([512, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for encoder.down.3.block.0.conv1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.0.norm2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.0.norm2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.0.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for encoder.down.3.block.0.conv2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.1.norm1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.1.norm1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.1.conv1.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for encoder.down.3.block.1.conv1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.1.norm2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.1.norm2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.down.3.block.1.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for encoder.down.3.block.1.conv2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for encoder.conv_out.weight: copying a param with shape torch.Size([4, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 3, 3]).
size mismatch for encoder.conv_out.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.conv_in.weight: copying a param with shape torch.Size([512, 4, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 256, 3, 3]).
size mismatch for decoder.up.0.block.0.norm1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.0.block.0.norm1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.0.block.0.conv1.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.block.0.conv1.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]).
size mismatch for decoder.up.1.block.0.conv1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.0.norm2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.0.norm2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.0.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.block.0.conv2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.1.norm1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.1.norm1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.1.conv1.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.block.1.conv1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.1.norm2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.1.norm2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.1.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.block.1.conv2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.2.norm1.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.2.norm1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.2.conv1.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.block.2.conv1.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.2.norm2.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.2.norm2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.block.2.conv2.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.block.2.conv2.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.1.upsample.conv.weight: copying a param with shape torch.Size([256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
size mismatch for decoder.up.1.upsample.conv.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([128]).
size mismatch for decoder.up.2.block.0.norm1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.2.block.0.norm1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.2.block.0.conv1.weight: copying a param with shape torch.Size([256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.block.0.conv1.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 3, 3]).
size mismatch for decoder.up.3.block.0.conv1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.0.norm2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.0.norm2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.0.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.block.0.conv2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.1.norm1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.1.norm1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.1.conv1.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.block.1.conv1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.1.norm2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.1.norm2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.1.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.block.1.conv2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.2.norm1.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.2.norm1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.2.conv1.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.block.2.conv1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.2.norm2.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.2.norm2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.block.2.conv2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.block.2.conv2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for decoder.up.3.upsample.conv.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
size mismatch for decoder.up.3.upsample.conv.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for quantize.embedding.weight: copying a param with shape torch.Size([16384, 4]) from checkpoint, the shape in current model is torch.Size([16384, 256]).
size mismatch for quant_conv.weight: copying a param with shape torch.Size([4, 4, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]).
size mismatch for quant_conv.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([256]).
size mismatch for post_quant_conv.weight: copying a param with shape torch.Size([4, 4, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]).
size mismatch for post_quant_conv.bias: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([256]).
I've tried changing the size of the image it is generating to 380 by 380 but it doesn't seem to be doing anything.
I am using windows 10 with an rtx 3060ti if that info is useful.
I seem to have fixed the issue by redownloading the .ckpt and .yaml files, but now it has just stopped at the line after "running with hinge loss." The line after it now says "Restored from checkpoints/vqgan_imagenet_f16_16384" where it seems to have frozen.
I seem to have fixed the issue, I redid the setup following the video and noticed that I had missed installing the MPEG portion. I also had to update the anaconda version, as it was showing that the one I installed wasn't the latest version. Not sure how that happened considering that I installed it from the anaconda website. Either way, it is working now.