code xformer issue

[archimedesinstitute]

Warning: CodeFormer not found at path /content/gdrive/MyDrive/sd/stablediffusion/src/codeformer/inference_codeformer.py LatentDiffusion: Running in v-prediction mode DiffusionWrapper has 865.91 M params. Loading weights [f5772f3f] from /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion/MintaSharedModels/Fortuna_4500realism.ckpt Traceback (most recent call last): File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 191, in webui() File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 131, in webui initialize() File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 61, in initialize modules.sd_models.load_model() File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 261, in load_model load_model_weights(sd_model, checkpoint_info) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 192, in load_model_weights model.load_state_dict(sd, strict=False) File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1604, 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.input_blocks.1.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.input_blocks.1.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.input_blocks.2.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.input_blocks.2.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.input_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.input_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.input_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.input_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.input_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.input_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.input_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.input_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.middle_block.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.middle_block.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]). size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]). size mismatch for model.diffusion_model.output_blocks.6.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.output_blocks.6.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.output_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.output_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.output_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]). size mismatch for model.diffusion_model.output_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]). size mismatch for model.diffusion_model.output_blocks.9.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.output_blocks.9.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.output_blocks.10.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.output_blocks.10.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.output_blocks.11.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]). size mismatch for model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]). size mismatch for model.diffusion_model.output_blocks.11.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).

[TheLastBen]

remove the folder sd from your gdrive and use this link https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb

[rektobot]

im getting 11.97it/s now so whatever you did ben, it worked. xformers isnt crapping the bed anymore and i moved the wheel from the modules folder to the main webui directory so maybe that helped. and i unquoted my commandline args 🤷‍♂️

[archimedesinstitute]

Fix temporarily worked, but it seems I have to delete and reinstall every other use. This is the most recent error

Traceback (most recent call last): File "/content/convertosd.py", line 209, in unet_state_dict = torch.load(unet_path, map_location='cpu') File "/usr/local/lib/python3.8/dist-packages/torch/serialization.py", line 699, in load with _open_file_like(f, 'rb') as opened_file: File "/usr/local/lib/python3.8/dist-packages/torch/serialization.py", line 230, in _open_file_like return _open_file(name_or_buffer, mode) File "/usr/local/lib/python3.8/dist-packages/torch/serialization.py", line 211, in init super(_open_file, self).init(open(name, mode)) FileNotFoundError: [Errno 2] No such file or directory: '/content/stable-diffusion-V2/unet/diffusion_pytorch_model.bin' Something went wrong, try again

[TheLastBen]

in which colab ?

[archimedesinstitute]

I used the most recently updated link for Automatic 1111.

[TheLastBen]

do a clean run, this error should happen, I just tested it with the latest colab