Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Error saving merged models: "KeyError: "sd_merge_recipe" #8

Closed
CCpt5 opened this issue Sep 12, 2023 · 6 comments
Closed

Error saving merged models: "KeyError: "sd_merge_recipe" #8

CCpt5 opened this issue Sep 12, 2023 · 6 comments
Assignees
@wkpark
Labels
bug Something isn't working
Milestone
Relase 1.0.0

Comments

@CCpt5
Copy link

CCpt5 commented Sep 12, 2023 •
edited
Loading

The save current merge model feature hasn't yet worked for me. In earlier versions I'd end up w/ a checkpoint that would come up as mostly "junk" data when loaded into the "model toolkit" extension. I checked them there as they were odd sizes and did not work in the app or for training. Those files would be generated if I unticked "Safetensors". Leaving that ticked gave a different error and failed to generate a checkpoint (sorry I don't have a log of that).

At the moment though when I try to save a model that has been created in an open session I'm getting the error "KeyError: 'sd_merge_recipe'":

 `To create a public link, set `share=True` in `launch()`.
Startup time: 1.7s (load scripts: 0.9s, create ui: 0.3s, gradio launch: 0.3s).
Traceback (most recent call last):
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 488, in run_predict
    output = await app.get_blocks().process_api(
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1431, in process_api
    result = await self.call_function(
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1103, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
    return await future
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
    result = context.run(func, *args)
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\gradio\utils.py", line 707, in wrapper
    response = f(*args, **kwargs)
  File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\extensions\sd-webui-model-mixer\scripts\model_mixer.py", line 811, in save_current_model
    metadata["sd_merge_recipe"] = json.dumps(metadata["sd_merge_recipe"])
KeyError: 'sd_merge_recipe'`
@wkpark wkpark self-assigned this Sep 12, 2023
@wkpark
Copy link
Owner

wkpark commented Sep 12, 2023

thanks for your reporting,

A merged model by Model mixer always sets the metadata, I guess you have tried to save is not a valid merge,
(Internally, a loaded model is stored in the shared.sd_model, and Model Mixer wrongly checked its validity (bug))
in this case, the correct behavior is to print out a "Current checkpoint is not a merged one." warning message.

fixed by commit 5fc7a42

@wkpark wkpark added the bug Something isn't working label Sep 12, 2023
@CCpt5
Copy link
Author

CCpt5 commented Sep 12, 2023 •
edited
Loading

I'm still having issues with saving a working model. I always get an error when "Safetensors" is toggled so I untoggle that to have it save a CKPT. Those saved files are broken/don't work though. Here's what the model toolkit extension shows for the one I just tried to save w/ Model Mixer:

111
2222

The error I get trying to save when Safetensors is toggled is:

To create a public link, set `share=True` in `launch()`.
Startup time: 11.4s (prepare environment: 1.9s, import torch: 1.4s, import gradio: 0.4s, setup paths: 0.3s, initialize shared: 0.2s, other imports: 0.3s, setup codeformer: 0.1s, load scripts: 1.9s, create ui: 4.6s, gradio launch: 0.2s).
INFO:sd_dynamic_prompts.dynamic_prompting:Prompt matrix will create 3 images in a total of 3 batches.
100%|██████████████████████████████████████████████████████████████████████████████████| 43/43 [00:14<00:00,  2.90it/s]
 14%|███████████▌                                                                       | 6/43 [00:02<00:16,  2.26it/s]
Total progress:  38%|████████████████████████▋                                        | 49/129 [00:22<00:35,  2.22it/s]
INFO:sd_dynamic_prompts.dynamic_prompting:Prompt matrix will create 3 images in a total of 3 batches.<00:44,  1.80it/s]
100%|██████████████████████████████████████████████████████████████████████████████████| 43/43 [00:14<00:00,  3.01it/s]
 86%|██████████████████████████████████████████████████████████████████████▌           | 37/43 [00:12<00:02,  2.97it/s]
Total progress:  62%|████████████████████████████████████████▎                        | 80/129 [00:31<00:19,  2.54it/s]
config hash =  1ab76befc9a272ddf7e354031543e84dca11a74123a63044977a796f111e2f37       | 80/129 [00:31<00:15,  3.17it/s]
  - mm_use [True, False, False, False, False]
  - model_a SDXL\Star Wars Things (SWThings)-step00001000.safetensors [d27a0f7c49]
  - base_model None
  - max_models 5
  - models ['SDXL\\Star Wars Things (SWThings)-step00002500.safetensors']
  - modes ['Sum']
  - usembws [[]]
  - weights ['0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5']
  - alpha [0.5]
  - adjust
model_a = SDXL_Star Wars Things (SWThings)-step00001000
Loading from file e:\Stable Diffusion Checkpoints\SDXL\Star Wars Things (SWThings)-step00001000.safetensors...
isxl = True
compact_mode =  False
Loading model SDXL_Star Wars Things (SWThings)-step00002500...
Loading from file e:\Stable Diffusion Checkpoints\SDXL\Star Wars Things (SWThings)-step00002500.safetensors...
Calculating sha256 for e:\Stable Diffusion Checkpoints\SDXL\Star Wars Things (SWThings)-step00002500.safetensors: 5b931543b7a1520aa4451b2cc20d76544ca9f861fa6428f231c39618fe60e14d
mode = Sum, alpha = 0.5
Stage #1/2: 100%|█████████████████████████████████████████████████████████████████| 2515/2515 [00:07<00:00, 328.32it/s]
Check uninitialized #2/2: 100%|███████████████████████████████████████████████| 2515/2515 [00:00<00:00, 1257591.15it/s]
Save unchanged weights #2/2: 0it [00:00, ?it/s]
Creating model from config: D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\repositories\generative-models\configs\inference\sd_xl_base.yaml
Loading VAE weights specified in settings: D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\models\VAE\sdxl_vae.safetensors
Applying attention optimization: sdp... done.
Model loaded in 2.0s (create model: 0.2s, apply weights to model: 1.5s, load VAE: 0.1s).
INFO:sd_dynamic_prompts.dynamic_prompting:Prompt matrix will create 3 images in a total of 3 batches.
100%|██████████████████████████████████████████████████████████████████████████████████| 43/43 [00:14<00:00,  2.92it/s]
100%|██████████████████████████████████████████████████████████████████████████████████| 43/43 [00:14<00:00,  3.02it/s]
100%|██████████████████████████████████████████████████████████████████████████████████| 43/43 [00:14<00:00,  3.02it/s]
Total progress: 100%|████████████████████████████████████████████████████████████████| 129/129 [00:51<00:00,  2.51it/s]
load from shared.sd_model..██████████████████████████████████████████████████████████| 129/129 [00:51<00:00,  3.21it/s]
Saving...
ERROR: Couldn't saved:D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\models\Stable-diffusion\test-delete-me.fp16.safetensors,ERROR is You are trying to save a non contiguous tensor: `model.diffusion_model.input_blocks.0.0.weight` which is not allowed. It either means you are trying to save tensors which are reference of each other in which case it's recommended to save only the full tensors, and reslice at load time, or simply call `.contiguous()` on your tensor to pack it before saving.

I've also run into this error complaining "'NoneType' object has no attribute 'lowvram'", but I don't recall the order to which that came up. I saw it yesterday also. I'm running A1111 on a very high end workstation w/ 64gb RAM and a 4090 (if that matters).

To create a public link, set `share=True` in `launch()`.
Startup time: 11.4s (prepare environment: 1.9s, import torch: 1.4s, import gradio: 0.4s, setup paths: 0.3s, initialize shared: 0.2s, other imports: 0.3s, setup codeformer: 0.1s, load scripts: 1.9s, create ui: 4.7s, gradio launch: 0.2s).
Loading model SDXL\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00001200.safetensors [bac56bff31] (2 out of 3)
Loading weights [bac56bff31] from e:\Stable Diffusion Checkpoints\SDXL\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00001200.safetensors
Creating model from config: D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\repositories\generative-models\configs\inference\sd_xl_base.yaml
Loading VAE weights specified in settings: D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\models\VAE\sdxl_vae.safetensors
Applying attention optimization: sdp... done.
Model loaded in 9.5s (load weights from disk: 0.6s, create model: 0.2s, apply weights to model: 8.2s, load VAE: 0.2s).
config hash =  3d18f7ea37b77bfe3300519f8340508136d10c86c0d2dd72f41f53c1eb056567
  - mm_use [True, True, False, False, False]
  - model_a SDXL\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00001200.safetensors [bac56bff31]
  - base_model None
  - max_models 5
  - models ['SDXL\\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00000900.safetensors [97944cdbc6]', 'SDXL\\2023-08-31 - Psych Rooms - psychrooms artstyle - 13img - TXT on - Batch 4 - 40rep - Bucket-step00001050.safetensors']
  - modes ['Sum', 'Sum']
  - usembws [[], []]
  - weights ['0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', '0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5']
  - alpha [0.5, 0.5]
  - adjust
model_a = SDXL_2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00001200
Loading SDXL\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00001200.safetensors [bac56bff31] from loaded model...
isxl = False
compact_mode =  False
Loading model SDXL_2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00000900...
Loading from file e:\Stable Diffusion Checkpoints\SDXL\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00000900.safetensors...
mode = Sum, alpha = 0.5
Stage #1/3: 100%|█████████████████████████████████████████████████████████████████| 3103/3103 [00:05<00:00, 530.17it/s]
Check uninitialized #2/3: 100%|███████████████████████████████████████████████| 3103/3103 [00:00<00:00, 1034243.91it/s]
Loading model SDXL_2023-08-31 - Psych Rooms - psychrooms artstyle - 13img - TXT on - Batch 4 - 40rep - Bucket-step00001050...
Loading from file e:\Stable Diffusion Checkpoints\SDXL\2023-08-31 - Psych Rooms - psychrooms artstyle - 13img - TXT on - Batch 4 - 40rep - Bucket-step00001050.safetensors...
Calculating sha256 for e:\Stable Diffusion Checkpoints\SDXL\2023-08-31 - Psych Rooms - psychrooms artstyle - 13img - TXT on - Batch 4 - 40rep - Bucket-step00001050.safetensors: 75769d480d052f535871d4327f658d75a6c18338bd2cd491e95a1e9cadc45b98
mode = Sum, alpha = 0.5
Stage #3/3: 100%|█████████████████████████████████████████████████████████████████| 3103/3103 [00:04<00:00, 621.77it/s]
Save unchanged weights #3/3: 0it [00:00, ?it/s]
Creating model from config: D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\configs\v1-inference.yaml
FATAL: Fail to load_model(). fallback load load_model_weights()... Error(s) in loading state_dict for LatentDiffusion:
        size mismatch for model.diffusion_model.input_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        size mismatch for model.diffusion_model.input_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        size mismatch for model.diffusion_model.input_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        size mismatch for model.diffusion_model.input_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        size mismatch for model.diffusion_model.input_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.input_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.input_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.input_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.middle_block.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.middle_block.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.2.0.in_layers.0.weight: copying a param with shape torch.Size([1920]) 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([1920]) 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([1280, 1920, 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.skip_connection.weight: copying a param with shape torch.Size([1280, 1920, 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.in_layers.0.weight: copying a param with shape torch.Size([1920]) 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([1920]) 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([640, 1920, 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([640]) 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([640, 1280]) 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([640]) 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([640]) 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([640]) 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([640, 640, 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([640]) 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([640, 1920, 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([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.norm.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.norm.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn1.to_q.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_k.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_v.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.0.proj.weight: copying a param with shape torch.Size([5120, 640]) from checkpoint, the shape in current model is torch.Size([10240, 1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.0.proj.bias: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([10240]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.2.weight: copying a param with shape torch.Size([640, 2560]) from checkpoint, the shape in current model is torch.Size([1280, 5120]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_q.weight: copying a param with shape torch.Size([640, 640]) 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([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm1.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm1.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm2.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm3.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm3.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.bias: copying a param with shape torch.Size([640]) 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([1280]) 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([1280]) 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([640, 1280, 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([640]) 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([640, 1280]) 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([640]) 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([640]) 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([640]) 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([640, 640, 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([640]) 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([640, 1280, 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([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.norm.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.norm.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn1.to_q.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_k.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_v.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.0.proj.weight: copying a param with shape torch.Size([5120, 640]) from checkpoint, the shape in current model is torch.Size([10240, 1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.0.proj.bias: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([10240]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.2.weight: copying a param with shape torch.Size([640, 2560]) from checkpoint, the shape in current model is torch.Size([1280, 5120]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_q.weight: copying a param with shape torch.Size([640, 640]) 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([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm1.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm1.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm2.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm3.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm3.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.bias: copying a param with shape torch.Size([640]) 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([960]) 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([960]) 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([640, 960, 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([640]) 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([640, 1280]) 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([640]) 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([640]) 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([640]) 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([640, 640, 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([640]) 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([640, 960, 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([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.norm.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.norm.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn1.to_q.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_k.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_v.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.0.proj.weight: copying a param with shape torch.Size([5120, 640]) from checkpoint, the shape in current model is torch.Size([10240, 1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.0.proj.bias: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([10240]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.2.weight: copying a param with shape torch.Size([640, 2560]) from checkpoint, the shape in current model is torch.Size([1280, 5120]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_q.weight: copying a param with shape torch.Size([640, 640]) 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([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm1.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm1.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm2.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm3.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm3.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.2.conv.weight: copying a param with shape torch.Size([640, 640, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
        size mismatch for model.diffusion_model.output_blocks.5.2.conv.bias: copying a param with shape torch.Size([640]) 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([960]) 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([960]) 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([320, 960, 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([320]) 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([320, 1280]) 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([320]) 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([320]) 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([320]) 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([320, 320, 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([320]) 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([320, 960, 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([320]) 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([640]) 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([640]) 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([320, 640, 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([320]) 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([320, 1280]) 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([320]) 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([320]) 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([320]) 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([320, 320, 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([320]) 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([320, 640, 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([320]) 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([640]) 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([640]) 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([320, 640, 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([320]) 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([320, 1280]) 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([320]) 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([320]) 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([320]) 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([320, 320, 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([320]) 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([320, 640, 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([320]) from checkpoint, the shape in current model is torch.Size([640]).
*** Error running before_process: D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\extensions\sd-webui-model-mixer\scripts\model_mixer.py
    Traceback (most recent call last):
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\extensions\sd-webui-model-mixer\scripts\model_mixer.py", line 1648, in before_process
        sd_models.load_model(checkpoint_info=checkpoint_info, already_loaded_state_dict=state_dict)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_models.py", line 626, in load_model
        load_model_weights(sd_model, checkpoint_info, state_dict, timer)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_models.py", line 353, in load_model_weights
        model.load_state_dict(state_dict, strict=False)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_disable_initialization.py", line 223, in <lambda>
        module_load_state_dict = self.replace(torch.nn.Module, 'load_state_dict', lambda *args, **kwargs: load_state_dict(module_load_state_dict, *args, **kwargs))
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_disable_initialization.py", line 221, in load_state_dict
        original(module, state_dict, strict=strict)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 2041, 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.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        size mismatch for model.diffusion_model.input_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        size mismatch for model.diffusion_model.input_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([640, 768]).
        size mismatch for model.diffusion_model.input_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([640, 640, 1, 1]).
        size mismatch for model.diffusion_model.input_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.input_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.input_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        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, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.input_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.middle_block.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.middle_block.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.2.0.in_layers.0.weight: copying a param with shape torch.Size([1920]) 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([1920]) 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([1280, 1920, 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.skip_connection.weight: copying a param with shape torch.Size([1280, 1920, 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.in_layers.0.weight: copying a param with shape torch.Size([1920]) 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([1920]) 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([640, 1920, 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([640]) 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([640, 1280]) 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([640]) 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([640]) 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([640]) 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([640, 640, 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([640]) 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([640, 1920, 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([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.norm.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.norm.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn1.to_q.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_k.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_v.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.0.proj.weight: copying a param with shape torch.Size([5120, 640]) from checkpoint, the shape in current model is torch.Size([10240, 1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.0.proj.bias: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([10240]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.2.weight: copying a param with shape torch.Size([640, 2560]) from checkpoint, the shape in current model is torch.Size([1280, 5120]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.ff.net.2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_q.weight: copying a param with shape torch.Size([640, 640]) 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([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm1.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm1.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm2.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm3.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.norm3.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.bias: copying a param with shape torch.Size([640]) 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([1280]) 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([1280]) 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([640, 1280, 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([640]) 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([640, 1280]) 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([640]) 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([640]) 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([640]) 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([640, 640, 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([640]) 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([640, 1280, 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([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.norm.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.norm.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn1.to_q.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_k.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_v.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.0.proj.weight: copying a param with shape torch.Size([5120, 640]) from checkpoint, the shape in current model is torch.Size([10240, 1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.0.proj.bias: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([10240]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.2.weight: copying a param with shape torch.Size([640, 2560]) from checkpoint, the shape in current model is torch.Size([1280, 5120]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.ff.net.2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_q.weight: copying a param with shape torch.Size([640, 640]) 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([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm1.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm1.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm2.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm3.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.norm3.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.bias: copying a param with shape torch.Size([640]) 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([960]) 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([960]) 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([640, 960, 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([640]) 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([640, 1280]) 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([640]) 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([640]) 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([640]) 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([640, 640, 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([640]) 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([640, 960, 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([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.norm.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.norm.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn1.to_q.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_k.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_v.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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.attn1.to_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.0.proj.weight: copying a param with shape torch.Size([5120, 640]) from checkpoint, the shape in current model is torch.Size([10240, 1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.0.proj.bias: copying a param with shape torch.Size([5120]) from checkpoint, the shape in current model is torch.Size([10240]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.2.weight: copying a param with shape torch.Size([640, 2560]) from checkpoint, the shape in current model is torch.Size([1280, 5120]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.ff.net.2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_q.weight: copying a param with shape torch.Size([640, 640]) 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([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 2048]) from checkpoint, the shape in current model is torch.Size([1280, 768]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_out.0.weight: copying a param with shape torch.Size([640, 640]) 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_out.0.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm1.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm1.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm2.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm2.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm3.weight: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.norm3.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 1, 1]).
        size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.bias: copying a param with shape torch.Size([640]) from checkpoint, the shape in current model is torch.Size([1280]).
        size mismatch for model.diffusion_model.output_blocks.5.2.conv.weight: copying a param with shape torch.Size([640, 640, 3, 3]) from checkpoint, the shape in current model is torch.Size([1280, 1280, 3, 3]).
        size mismatch for model.diffusion_model.output_blocks.5.2.conv.bias: copying a param with shape torch.Size([640]) 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([960]) 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([960]) 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([320, 960, 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([320]) 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([320, 1280]) 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([320]) 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([320]) 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([320]) 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([320, 320, 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([320]) 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([320, 960, 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([320]) 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([640]) 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([640]) 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([320, 640, 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([320]) 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([320, 1280]) 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([320]) 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([320]) 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([320]) 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([320, 320, 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([320]) 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([320, 640, 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([320]) 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([640]) 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([640]) 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([320, 640, 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([320]) 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([320, 1280]) 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([320]) 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([320]) 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([320]) 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([320, 320, 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([320]) 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([320, 640, 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([320]) from checkpoint, the shape in current model is torch.Size([640]).

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\scripts.py", line 611, in before_process
        script.before_process(p, *script_args)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\extensions\sd-webui-model-mixer\scripts\model_mixer.py", line 1653, in before_process
        sd_models.load_model_weights(shared.sd_model, checkpoint_info, theta_0, timer)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_models.py", line 346, in load_model_weights
        model.is_sdxl = hasattr(model, 'conditioner')
    AttributeError: 'NoneType' object has no attribute 'is_sdxl'

---
*** Error completing request
*** Arguments: ('task(oouwen0nur1qgvi)', 'psychrooms artstye in london. ', '', [], 43, 'DPM++ 2M Karras', 3, 1, 5, 1088, 1880, False, 0.14, 1.45, 'Lanczos', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x00000154B1B85C90>, 0, False, '', 0.8, -1, False, -1, 0, 0, 0, False, 7, 100, 'Constant', 0, 'Constant', 0, 4, True, 'MEAN', 'AD', 1, True, False, 1, False, False, False, 1.1, 1.5, 100, 0.7, False, False, True, False, False, 0, 'Gustavosta/MagicPrompt-Stable-Diffusion', '', False, {'ad_model': 'face_yolov8n.pt', 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'inpaint_global_harmonious', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.3, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.4, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': False, 'ad_inpaint_width': 512, 'ad_inpaint_height': 512, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'inpaint_global_harmonious', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, <scripts.controlnet_ui.controlnet_ui_group.UiControlNetUnit object at 0x00000154B1B86920>, <scripts.controlnet_ui.controlnet_ui_group.UiControlNetUnit object at 0x00000154B1B87700>, <scripts.controlnet_ui.controlnet_ui_group.UiControlNetUnit object at 0x00000154B1B864D0>, True, 'SDXL\\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00001200.safetensors [bac56bff31]', 'None', 5, '', True, True, False, False, False, 'SDXL\\2023-09-10 - PsychRooms Artstyle - 22IMG - TXT On - 40rep - B4-step00000900.safetensors [97944cdbc6]', 'SDXL\\2023-08-31 - Psych Rooms - psychrooms artstyle - 13img - TXT on - Batch 4 - 40rep - Bucket-step00001050.safetensors', 'SDXL\\2023-08-31 - Psych Rooms - psychrooms artstyle - 13img - TXT on - Batch 4 - 40rep - Bucket-step00000800.safetensors', 'None', 'None', 'Sum', 'Sum', 'Sum', 'Sum', 'Sum', 0.5, 0.5, 0.5, 0.5, 0.5, True, True, True, True, True, [], [], [], [], [], [], [], [], [], [], '0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', '0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', '0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', '0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', '0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5', False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, 50) {}
    Traceback (most recent call last):
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\processing.py", line 719, in process_images
        sd_models.reload_model_weights()
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_models.py", line 732, in reload_model_weights
        sd_model = reuse_model_from_already_loaded(sd_model, checkpoint_info, timer)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_models.py", line 681, in reuse_model_from_already_loaded
        send_model_to_cpu(sd_model)
      File "D:\Stable-Diffusion-Webui-Dev\sdxl\stable-diffusion-webui\modules\sd_models.py", line 541, in send_model_to_cpu
        if m.lowvram:
    AttributeError: 'NoneType' object has no attribute 'lowvram'

@wkpark
Copy link
Owner

wkpark commented Sep 13, 2023

same issue here, this is another issue.
my case: use --medvram-sdxl, in this case, internal shared.sd_model is the loaded model. but it's sizes are mismatched.

@wkpark
Copy link
Owner

wkpark commented Sep 13, 2023

fixed! #11 will be merged shortly.

@CCpt5
Copy link
Author

CCpt5 commented Sep 13, 2023

Played around with it for the last couple of hours and seems to be working great now.

Good job!

@wkpark wkpark added this to the Relase 1.0.0 milestone Sep 13, 2023
@wkpark wkpark closed this as completed Sep 13, 2023
@wkpark
Copy link
Owner

wkpark commented Sep 16, 2023 •
edited
Loading

#18
for some cases, merged models can't be saved correctly. (for example, after using LoRAs)
in these cases, you can use "save model" option in the "Settings"->"Model Mixer".

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees

@wkpark wkpark

Labels
bug Something isn't working
Projects
None yet
Milestone
Relase 1.0.0
Development

No branches or pull requests
2 participants
@wkpark @CCpt5