semantic-driven image synthesis failed

[HUuxiaobin]

Dear author,

Thanks so much for your great contribution in image synthesis community. Inspired by your semantic-to-image demo in figure 8 of paper, I would like to reshow the figure 8 results to demonstrate the effectiveness of semantic-to-image synthesis. But I failed to get the realistic image from the semantic when I use the zoom-in semantic image of figure 8 and the prompt "A fantasy lake under the sunset'' with the checkpoint of stable-diffusion-v1-1. I am wondering if you could help me to fix this problem and then enlarge your great influence in segmentation domain. Have a nice day!

best
TU Munich

[KostyaAtarik]

I'm not sure, but have you tried the models semantic_synthesis512 and semantic_synthesis256 from https://github.com/CompVis/stable-diffusion/blob/main/scripts/download_models.sh ?

[HUuxiaobin]

Thanks for your quick reply. I run the segmentation-to-image script 'python scripts/img2img.py --prompt "A fantasy lake under the sunset" --init-img ./mask/case2.png --strength 0.8' and the models are from semantic_synthesis256 model and a 512 model. The error occurred as follows:
m, u = model.load_state_dict(sd, strict=False)
File "/root/anaconda3/envs/ldm/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1497, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for LatentDiffusion:
size mismatch for model.diffusion_model.time_embed.0.weight: copying a param with shape torch.Size([512, 128]) from checkpoint, the shape in current model is torch.Size([1280, 320]).
size mismatch for model.diffusion_model.time_embed.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.time_embed.2.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.time_embed.2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.0.0.weight: copying a param with shape torch.Size([128, 6, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 4, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.0.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.in_layers.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.1.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([320, 1280]).
size mismatch for model.diffusion_model.input_blocks.1.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.1.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.1.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.in_layers.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.2.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([320, 1280]).
size mismatch for model.diffusion_model.input_blocks.2.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.2.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.2.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.3.0.op.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([320, 320, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.3.0.op.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.4.0.in_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.4.0.in_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.input_blocks.4.0.in_layers.2.weight: copying a param with shape torch.Size([512, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 320, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.4.0.in_layers.2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.4.0.emb_layers.1.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([640, 1280]).
size mismatch for model.diffusion_model.input_blocks.4.0.emb_layers.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.4.0.out_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.4.0.out_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.4.0.out_layers.3.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.4.0.out_layers.3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.4.0.skip_connection.weight: copying a param with shape torch.Size([512, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 320, 1, 1]).
size mismatch for model.diffusion_model.input_blocks.4.0.skip_connection.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.in_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.in_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.in_layers.2.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.5.0.in_layers.2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.emb_layers.1.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([640, 1280]).
size mismatch for model.diffusion_model.input_blocks.5.0.emb_layers.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.out_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.out_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.5.0.out_layers.3.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.5.0.out_layers.3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.6.0.op.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.6.0.op.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.7.0.in_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.7.0.in_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.input_blocks.7.0.in_layers.2.weight: copying a param with shape torch.Size([1024, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 640, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.7.0.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.7.0.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.7.0.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.7.0.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.7.0.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.7.0.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.7.0.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.7.0.skip_connection.weight: copying a param with shape torch.Size([1024, 512, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 640, 1, 1]).
size mismatch for model.diffusion_model.input_blocks.7.0.skip_connection.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.in_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.in_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.in_layers.2.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.8.0.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.input_blocks.8.0.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.input_blocks.8.0.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.in_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.in_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.in_layers.2.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.middle_block.0.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.middle_block.0.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.0.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.middle_block.0.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.1.norm.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.1.norm.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.1.proj_out.weight: copying a param with shape torch.Size([1024, 1024, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
size mismatch for model.diffusion_model.middle_block.1.proj_out.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.in_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.in_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.in_layers.2.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.middle_block.2.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.middle_block.2.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.middle_block.2.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.middle_block.2.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.in_layers.0.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.0.0.in_layers.0.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.0.0.in_layers.2.weight: copying a param with shape torch.Size([1024, 2048, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.0.0.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.0.0.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.0.0.skip_connection.weight: copying a param with shape torch.Size([1024, 2048, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.0.0.skip_connection.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.in_layers.0.weight: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.1.0.in_layers.0.bias: copying a param with shape torch.Size([2048]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.1.0.in_layers.2.weight: copying a param with shape torch.Size([1024, 2048, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.1.0.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.1.0.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.1.0.skip_connection.weight: copying a param with shape torch.Size([1024, 2048, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.1.0.skip_connection.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.in_layers.0.weight: copying a param with shape torch.Size([1536]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.2.0.in_layers.0.bias: copying a param with shape torch.Size([1536]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.2.0.in_layers.2.weight: copying a param with shape torch.Size([1024, 1536, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.2.0.in_layers.2.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.emb_layers.1.weight: copying a param with shape torch.Size([1024, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.emb_layers.1.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.out_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.out_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.out_layers.3.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.2.0.out_layers.3.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.0.skip_connection.weight: copying a param with shape torch.Size([1024, 1536, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.2.0.skip_connection.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.2.1.conv.weight: copying a param with shape torch.Size([1024, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.2.1.conv.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.in_layers.0.weight: copying a param with shape torch.Size([1536]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.3.0.in_layers.0.bias: copying a param with shape torch.Size([1536]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.3.0.in_layers.2.weight: copying a param with shape torch.Size([512, 1536, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.3.0.in_layers.2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.emb_layers.1.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.emb_layers.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.out_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.out_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.out_layers.3.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.3.0.out_layers.3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.3.0.skip_connection.weight: copying a param with shape torch.Size([512, 1536, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.3.0.skip_connection.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.in_layers.0.weight: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.4.0.in_layers.0.bias: copying a param with shape torch.Size([1024]) from checkpoint, the shape in current model is torch.Size([2560]).
size mismatch for model.diffusion_model.output_blocks.4.0.in_layers.2.weight: copying a param with shape torch.Size([512, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.4.0.in_layers.2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.emb_layers.1.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.emb_layers.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.out_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.out_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.out_layers.3.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.4.0.out_layers.3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.4.0.skip_connection.weight: copying a param with shape torch.Size([512, 1024, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 2560, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.4.0.skip_connection.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.in_layers.0.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1920]).
size mismatch for model.diffusion_model.output_blocks.5.0.in_layers.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1920]).
size mismatch for model.diffusion_model.output_blocks.5.0.in_layers.2.weight: copying a param with shape torch.Size([512, 640, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1920, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.5.0.in_layers.2.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.emb_layers.1.weight: copying a param with shape torch.Size([512, 512]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.emb_layers.1.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.out_layers.0.weight: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.out_layers.0.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.out_layers.3.weight: copying a param with shape torch.Size([512, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.5.0.out_layers.3.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.5.0.skip_connection.weight: copying a param with shape torch.Size([512, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1920, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.5.0.skip_connection.bias: copying a param with shape torch.Size([512]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.6.0.in_layers.0.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1920]).
size mismatch for model.diffusion_model.output_blocks.6.0.in_layers.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1920]).
size mismatch for model.diffusion_model.output_blocks.6.0.in_layers.2.weight: copying a param with shape torch.Size([128, 640, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 1920, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.6.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.6.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([640, 1280]).
size mismatch for model.diffusion_model.output_blocks.6.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.6.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.6.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.6.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.6.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.6.0.skip_connection.weight: copying a param with shape torch.Size([128, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 1920, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.6.0.skip_connection.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.7.0.in_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.7.0.in_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([1280]).
size mismatch for model.diffusion_model.output_blocks.7.0.in_layers.2.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 1280, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.7.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.7.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([640, 1280]).
size mismatch for model.diffusion_model.output_blocks.7.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.7.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.7.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.7.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.7.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.7.0.skip_connection.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 1280, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.7.0.skip_connection.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.8.0.in_layers.0.weight: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([960]).
size mismatch for model.diffusion_model.output_blocks.8.0.in_layers.0.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([960]).
size mismatch for model.diffusion_model.output_blocks.8.0.in_layers.2.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 960, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.8.0.in_layers.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.8.0.emb_layers.1.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([640, 1280]).
size mismatch for model.diffusion_model.output_blocks.8.0.emb_layers.1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.8.0.out_layers.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.8.0.out_layers.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.8.0.out_layers.3.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([640, 640, 3, 3]).
size mismatch for model.diffusion_model.output_blocks.8.0.out_layers.3.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.output_blocks.8.0.skip_connection.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 960, 1, 1]).
size mismatch for model.diffusion_model.output_blocks.8.0.skip_connection.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([640]).
size mismatch for model.diffusion_model.out.0.weight: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.out.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([320]).
size mismatch for model.diffusion_model.out.2.weight: copying a param with shape torch.Size([3, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([4, 320, 3, 3]).
size mismatch for model.diffusion_model.out.2.bias: copying a param with shape torch.Size([3]) from checkpoint, the shape in current model is torch.Size([4]).
size mismatch for first_stage_model.encoder.conv_out.weight: copying a param with shape torch.Size([3, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([8, 512, 3, 3]).
size mismatch for first_stage_model.encoder.conv_out.bias: copying a param with shape torch.Size([3]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for first_stage_model.decoder.conv_in.weight: copying a param with shape torch.Size([512, 3, 3, 3]) from checkpoint, the shape in current model is torch.Size([512, 4, 3, 3]).
size mismatch for first_stage_model.quant_conv.weight: copying a param with shape torch.Size([3, 3, 1, 1]) from checkpoint, the shape in current model is torch.Size([8, 8, 1, 1]).
size mismatch for first_stage_model.quant_conv.bias: copying a param with shape torch.Size([3]) from checkpoint, the shape in current model is torch.Size([8]).
size mismatch for first_stage_model.post_quant_conv.weight: copying a param with shape torch.Size([3, 3, 1, 1]) from checkpoint, the shape in current model is torch.Size([4, 4, 1, 1]).
size mismatch for first_stage_model.post_quant_conv.bias: copying a param with shape torch.Size([3]) from checkpoint, the shape in current model is torch.Size([4]).

Is this problem of first-stage-model? which model should I use in first stage ?

wget -O models/first_stage_models/kl-f4/model.zip https://ommer-lab.com/files/latent-diffusion/kl-f4.zip
wget -O models/first_stage_models/kl-f8/model.zip https://ommer-lab.com/files/latent-diffusion/kl-f8.zip
wget -O models/first_stage_models/kl-f16/model.zip https://ommer-lab.com/files/latent-diffusion/kl-f16.zip
wget -O models/first_stage_models/kl-f32/model.zip https://ommer-lab.com/files/latent-diffusion/kl-f32.zip
wget -O models/first_stage_models/vq-f4/model.zip https://ommer-lab.com/files/latent-diffusion/vq-f4.zip
wget -O models/first_stage_models/vq-f4-noattn/model.zip https://ommer-lab.com/files/latent-diffusion/vq-f4-noattn.zip
wget -O models/first_stage_models/vq-f8/model.zip https://ommer-lab.com/files/latent-diffusion/vq-f8.zip
wget -O models/first_stage_models/vq-f8-n256/model.zip https://ommer-lab.com/files/latent-diffusion/vq-f8-n256.zip
wget -O models/first_stage_models/vq-f16/model.zip https://ommer-lab.com/files/latent-diffusion/vq-f16.zip

thanks very much for your help. Have a nice day!

best regards

[bohnedan]

@HUuxiaobin I'm running into the very same error.
Did you accomplish to run the model checkpoint for semantic synthesis? I'm currently figuring, that the concatenation and torch shape need to be aligned with the UNet structure. I think therefore the semantic map needs to be encoded to match the latent image representation (probably 320²px in the downsized version according to the error, should be downsized by 4). Is this encoding process available anywhere? I only found it within inpaint.py. Besides that by reading the paper I'd say that the vq-f4 should be the correct first stage for the semantic synthesis.

[Hey-Sweety]

Hello, I am also working on the task of semantic image synthesis.
⭐May I ask which file should we run? Is it img2img. py?
⭐And how should the variable "config" be set to achieve the task of semantic synthesis? Should we use the yaml file in the configs folder or the yaml file in the models folder?
Thank you so much and looking forward to your reply.❤

[Noora555]

您好，我也在做语义图像合成的任务。 ⭐请问我们应该运行哪个文件？是 img2img 吗。py？ ⭐以及应该如何设置变量 “config” 来完成语义合成的任务呢？我们应该使用 configs 文件夹中的 yaml 文件还是 models 文件夹中的 yaml 文件？非常感谢您，并期待您的回复。 ❤

hello, I met the same problem. Have you solved it？❤