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calcmode normal doesnt work with smoothMT model #390

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boldoran opened this issue Jul 22, 2024 · 0 comments
Open

calcmode normal doesnt work with smoothMT model #390

boldoran opened this issue Jul 22, 2024 · 0 comments

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@boldoran
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boldoran commented Jul 22, 2024

as description reads, I cant merge a model previously merged with smoothMT in normal calcmode, it throws a Runtime error.
is this as intended? or is something not working? ive never used smoothMT before, but I kinda like the outcome i have now and would like to work further on it.
thanks.

"Traceback (most recent call last):
File "A:\AI\stable-diffusion\venv\lib\site-packages\gradio\routes.py", line 488, in run_predict
output = await app.get_blocks().process_api(
File "A:\AI\stable-diffusion\venv\lib\site-packages\gradio\blocks.py", line 1431, in process_api
result = await self.call_function(
File "A:\AI\stable-diffusion\venv\lib\site-packages\gradio\blocks.py", line 1103, in call_function
prediction = await anyio.to_thread.run_sync(
File "A:\AI\stable-diffusion\venv\lib\site-packages\anyio\to_thread.py", line 33, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "A:\AI\stable-diffusion\venv\lib\site-packages\anyio_backends_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "A:\AI\stable-diffusion\venv\lib\site-packages\anyio_backends_asyncio.py", line 807, in run
result = context.run(func, *args)
File "A:\AI\stable-diffusion\venv\lib\site-packages\gradio\utils.py", line 707, in wrapper
response = f(*args, **kwargs)
File "A:\AI\stable-diffusion\extensions\sd-webui-supermerger\scripts\mergers\xyplot.py", line 78, in numanager
result,currentmodel,xyimage,a,b,c= sgenxyplot(*allsets)
File "A:\AI\stable-diffusion\extensions\sd-webui-supermerger\scripts\mergers\xyplot.py", line 432, in sgenxyplot
_, currentmodel,modelid,theta_0, metadata =smerge(weights_a_in,weights_b_in, model_a,model_b,model_c, float(alpha),float(beta),mode,calcmode,
File "A:\AI\stable-diffusion\extensions\sd-webui-supermerger\scripts\mergers\mergers.py", line 457, in smerge
theta_0_a = torch.lerp(theta_0_a.to(torch.float32), theta_1[key].to(torch.float32), current_alpha).to(theta_0_a.dtype)
RuntimeError: The size of tensor a (64) must match the size of tensor b (128) at non-singleton dimension 0
"

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