Repository: stable-diffusion-webui
Issue: [버그]: WARNING[XFORMERS]
Labels: bug-report

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What happened?

Start Stable-Diffusion

WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:
    PyTorch 2.1.0+cu118 with CUDA 1106 (you have 2.1.0+cu121)
    Python  3.9.16 (you have 3.10.12)

### Steps to reproduce the problem

*** Error completing request
*** Arguments: ('task(3gwveqabb1mah2g)', '(masterpiece), (best quality), (realistic), RAW, ultra high res, highres, dslr, ultra detailed, cinematic lighting, detailed lighting, (photorealistic), 8k, UHD, hyper-realistic, Photograph, physically based rendering, lens flare,\n<lora:add_detail:0.3>, (ulzzang-6500-v1.1:0.2), (25 years old gorgeous beautiful Korean woman), (kpop idol), (korean beauty), (korean mixed), intricate details, beautiful face, Delicate eyes, realistic eyes, perfect body, lustrous skin, thigh gap, large breasts, covered nipples,\n(grinning, smiling), (wave hair:1.3), (spaghetti strap, tank top, crop top:1.5), (pencil skirt, cotton skirt:1.5), (very short and tight mini skirt:1.2), (show panties, socks, sneakers:1.2) (wind, trees , grass, lake:1.2), (one knee:1.3),', '(ng_deepnegative_v1_75t), (badhandv4:1.5), nsfw, (worst quality, low quality:1.3), (depth of field, blurry:1.2), (greyscale, monochrome), 3D face, nose, cropped, lowres, text, jpeg artifacts, signature, watermark, username, blurry, artist name, trademark, watermark, title, (tan, muscular, loli, petite, child, infant, toddlers, chibi, sd character), multiple view, Reference sheet,', [], 30, 'DPM++ SDE Karras', 1, 1, 7, 910, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x79d722750820>, 0, False, '', 0.8, 1779706928, False, -1, 0, 0, 0, UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), 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 "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 732, in process_images
        res = process_images_inner(p)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/batch_hijack.py", line 42, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 867, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 1140, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 235, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_common.py", line 261, in launch_sampling
        return func()
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 235, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/sampling.py", line 553, in sample_dpmpp_sde
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_cfg_denoiser.py", line 188, in forward
        x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 112, in forward
        eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 138, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_utils.py", line 26, in __call__
        return self.__sub_func(self.__orig_func, *args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_unet.py", line 48, in apply_model
        return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/models/diffusion/ddpm.py", line 858, in apply_model
        x_recon = self.model(x_noisy, t, **cond)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/models/diffusion/ddpm.py", line 1329, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_unet.py", line 91, in UNetModel_forward
        return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py", line 776, in forward
        h = module(h, emb, context)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py", line 84, in forward
        x = layer(x, context)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 334, in forward
        x = block(x, context=context[i])
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 269, in forward
        return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/util.py", line 114, in checkpoint
        return CheckpointFunction.apply(func, len(inputs), *args)
      File "/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py", line 539, in apply
        return super().apply(*args, **kwargs)  # type: ignore[misc]
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/util.py", line 129, in forward
        output_tensors = ctx.run_function(*ctx.input_tensors)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 272, in _forward
        x = self.attn1(self.norm1(x), context=context if self.disable_self_attn else None) + x
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_optimizations.py", line 496, in xformers_attention_forward
        out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=get_xformers_flash_attention_op(q, k, v))
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/__init__.py", line 223, in memory_efficient_attention
        return _memory_efficient_attention(
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/__init__.py", line 321, in _memory_efficient_attention
        return _memory_efficient_attention_forward(
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/__init__.py", line 337, in _memory_efficient_attention_forward
        op = _dispatch_fw(inp, False)
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 120, in _dispatch_fw
        return _run_priority_list(
      File "/usr/local/lib/python3.10/dist-packa

### What should have happened?

"Generate" Click to create an image

### Sysinfo

WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:
    PyTorch 2.1.0+cu118 with CUDA 1106 (you have 2.1.0+cu121)
    Python  3.9.16 (you have 3.10.12)
  Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers)
  

### What browsers do you use to access the UI ?

구글 크롬

### Console logs

```Shell
WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:
    PyTorch 2.1.0+cu118 with CUDA 1106 (you have 2.1.0+cu121)
    Python  3.9.16 (you have 3.10.12)
  Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers)
  Memory-efficient attention, SwiGLU, sparse and more won't be available.
  Set XFORMERS_MORE_DETAILS=1 for more details
ControlNet preprocessor location: /content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/downloads
2023-12-16 00:42:59,467 - ControlNet - INFO - ControlNet v1.1.422
2023-12-16 00:43:06,058 - ControlNet - INFO - ControlNet v1.1.422
Calculating sha256 for /content/temp_models/v1-5-pruned-emaonly.safetensors: Running on public URL: https://ee9c7e90841b805900.gradio.live
✔ Connected
Startup time: 210.5s (launcher: 1.6s, import torch: 9.4s, import gradio: 1.4s, setup paths: 42.4s, import ldm: 1.2s, initialize shared: 11.7s, other imports: 57.6s, setup codeformer: 16.8s, setup gfpgan: 0.6s, list SD models: 3.0s, load scripts: 52.6s, load upscalers: 1.4s, initialize extra networks: 3.4s, create ui: 2.3s, gradio launch: 4.9s, add APIs: 0.1s).
6ce0161689b3853acaa03779ec93eafe75a02f4ced659bee03f50797806fa2fa
Loading weights [6ce0161689] from /content/temp_models/v1-5-pruned-emaonly.safetensors
Creating model from config: /content/gdrive/MyDrive/sd/stable-diffusion-webui/configs/v1-inference.yaml
Applying attention optimization: xformers... done.
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/badhandv4.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/badhandv4.pt: 5e40d722fc3d0c2decb62debfaf8058db30ccdae9ab00ff64b183907b435708e
5e40d722fc3d0c2decb62debfaf8058db30ccdae9ab00ff64b183907b435708e
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ulzzang-6500-v1.1.bin: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ulzzang-6500-v1.1.bin: 8c1af299c7e8c2283892a7ad61a5fe5574e88c9c2ee77cd0cdfc0615155fa315
8c1af299c7e8c2283892a7ad61a5fe5574e88c9c2ee77cd0cdfc0615155fa315
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ulzzang-6500.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ulzzang-6500.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ulzzang-6500.pt: 66d481a222ee4638e254a411890f2a8716e4ce5c3e1b1957891c7628bbdeac78
66d481a222ee4638e254a411890f2a8716e4ce5c3e1b1957891c7628bbdeac78
66d481a222ee4638e254a411890f2a8716e4ce5c3e1b1957891c7628bbdeac78
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/negative_hand-neg.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/negative_hand-neg.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/negative_hand-neg.pt: 73b524a2da121eb1b7ad04dea11da286277813120700ff8f1d8522516f7b30ab
73b524a2da121eb1b7ad04dea11da286277813120700ff8f1d8522516f7b30ab
73b524a2da121eb1b7ad04dea11da286277813120700ff8f1d8522516f7b30ab
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ng_deepnegative_v1_75t.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ng_deepnegative_v1_75t.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/ng_deepnegative_v1_75t.pt: 54e7e4826d53949a3d0dde40aea023b1e456a618c608a7630e3999fd38f93245
54e7e4826d53949a3d0dde40aea023b1e456a618c608a7630e3999fd38f93245
54e7e4826d53949a3d0dde40aea023b1e456a618c608a7630e3999fd38f93245
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/bad-hands-5.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/bad-hands-5.pt: Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/embeddings/bad-hands-5.pt: aa7651be154c46a2f4868788ef84a92b3083b0c0c5c46f5012a56698bfd2a1ba
aa7651be154c46a2f4868788ef84a92b3083b0c0c5c46f5012a56698bfd2a1ba
aa7651be154c46a2f4868788ef84a92b3083b0c0c5c46f5012a56698bfd2a1ba
Model loaded in 29.8s (calculate hash: 13.2s, load weights from disk: 0.5s, create model: 9.8s, apply weights to model: 2.1s, load textual inversion embeddings: 3.6s, calculate empty prompt: 0.6s).
Restarting UI...
Closing server running on port: 7860
2023-12-16 00:44:38,560 - ControlNet - INFO - ControlNet v1.1.422
Running on public URL: https://6fbbf99473237a6a1f.gradio.live
✔ Connected
Startup time: 3.3s (load scripts: 0.7s, create ui: 0.5s, gradio launch: 2.0s, add APIs: 0.1s).
Loading VAE weights specified in settings: /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/VAE/vae-ft-mse-840000-ema-pruned.safetensors
Applying attention optimization: xformers... done.
VAE weights loaded.
Reusing loaded model v1-5-pruned-emaonly.safetensors [6ce0161689] to load hanimix_v12.safetensors
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion/hanimix_v12.safetensors: 79aa3397cc30676dbdbcfee6b21944a9eaafd5aa4882a95162957ca49a40d354
Loading weights [79aa3397cc] from /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion/hanimix_v12.safetensors
Loading VAE weights specified in settings: /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/VAE/vae-ft-mse-840000-ema-pruned.safetensors
Applying attention optimization: xformers... done.
Weights loaded in 36.2s (send model to cpu: 0.9s, calculate hash: 31.3s, load weights from disk: 1.4s, apply weights to model: 1.6s, load VAE: 0.4s, move model to device: 0.7s).
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/VAE/vae-ft-mse-840000-ema-pruned.safetensors: 735e4c3a447a3255760d7f86845f09f937809baa529c17370d83e4c3758f3c75
Calculating sha256 for /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Lora/add_detail.safetensors: 7c6bad76eb54e80ebe40f5a455b1cf7a743e09fe2fc1289cf333544e3aa071ce
  0% 0/30 [00:00<?, ?it/s]
*** Error completing request
*** Arguments: ('task(3gwveqabb1mah2g)', '(masterpiece), (best quality), (realistic), RAW, ultra high res, highres, dslr, ultra detailed, cinematic lighting, detailed lighting, (photorealistic), 8k, UHD, hyper-realistic, Photograph, physically based rendering, lens flare,\n<lora:add_detail:0.3>, (ulzzang-6500-v1.1:0.2), (25 years old gorgeous beautiful Korean woman), (kpop idol), (korean beauty), (korean mixed), intricate details, beautiful face, Delicate eyes, realistic eyes, perfect body, lustrous skin, thigh gap, large breasts, covered nipples,\n(grinning, smiling), (wave hair:1.3), (spaghetti strap, tank top, crop top:1.5), (pencil skirt, cotton skirt:1.5), (very short and tight mini skirt:1.2), (show panties, socks, sneakers:1.2) (wind, trees , grass, lake:1.2), (one knee:1.3),', '(ng_deepnegative_v1_75t), (badhandv4:1.5), nsfw, (worst quality, low quality:1.3), (depth of field, blurry:1.2), (greyscale, monochrome), 3D face, nose, cropped, lowres, text, jpeg artifacts, signature, watermark, username, blurry, artist name, trademark, watermark, title, (tan, muscular, loli, petite, child, infant, toddlers, chibi, sd character), multiple view, Reference sheet,', [], 30, 'DPM++ SDE Karras', 1, 1, 7, 910, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x79d722750820>, 0, False, '', 0.8, 1779706928, False, -1, 0, 0, 0, UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), UiControlNetUnit(enabled=False, module='none', model='None', weight=1, image=None, resize_mode='Crop and Resize', low_vram=False, processor_res=-1, threshold_a=-1, threshold_b=-1, guidance_start=0, guidance_end=1, pixel_perfect=False, control_mode='Balanced', save_detected_map=True), 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 "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/txt2img.py", line 55, in txt2img
        processed = processing.process_images(p)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 732, in process_images
        res = process_images_inner(p)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/batch_hijack.py", line 42, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 867, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 1140, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 235, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_common.py", line 261, in launch_sampling
        return func()
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 235, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/sampling.py", line 553, in sample_dpmpp_sde
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_cfg_denoiser.py", line 188, in forward
        x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 112, in forward
        eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 138, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_utils.py", line 26, in __call__
        return self.__sub_func(self.__orig_func, *args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_unet.py", line 48, in apply_model
        return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/models/diffusion/ddpm.py", line 858, in apply_model
        x_recon = self.model(x_noisy, t, **cond)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/models/diffusion/ddpm.py", line 1329, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_unet.py", line 91, in UNetModel_forward
        return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py", line 776, in forward
        h = module(h, emb, context)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py", line 84, in forward
        x = layer(x, context)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 334, in forward
        x = block(x, context=context[i])
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 269, in forward
        return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/util.py", line 114, in checkpoint
        return CheckpointFunction.apply(func, len(inputs), *args)
      File "/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py", line 539, in apply
        return super().apply(*args, **kwargs)  # type: ignore[misc]
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/util.py", line 129, in forward
        output_tensors = ctx.run_function(*ctx.input_tensors)
      File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 272, in _forward
        x = self.attn1(self.norm1(x), context=context if self.disable_self_attn else None) + x
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_optimizations.py", line 496, in xformers_attention_forward
        out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=get_xformers_flash_attention_op(q, k, v))
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/__init__.py", line 223, in memory_efficient_attention
        return _memory_efficient_attention(
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/__init__.py", line 321, in _memory_efficient_attention
        return _memory_efficient_attention_forward(
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/__init__.py", line 337, in _memory_efficient_attention_forward
        op = _dispatch_fw(inp, False)
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 120, in _dispatch_fw
        return _run_priority_list(
      File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 63, in _run_priority_list
        raise NotImplementedError(msg)
    NotImplementedError: No operator found for `memory_efficient_attention_forward` with inputs:
         query       : shape=(1, 7232, 8, 40) (torch.float16)
         key         : shape=(1, 7232, 8, 40) (torch.float16)
         value       : shape=(1, 7232, 8, 40) (torch.float16)
         attn_bias   : <class 'NoneType'>
         p           : 0.0
    `decoderF` is not supported because:
        xFormers wasn't build with CUDA support
        attn_bias type is <class 'NoneType'>
        operator wasn't built - see `python -m xformers.info` for more info
    `flshattF@0.0.0` is not supported because:
        xFormers wasn't build with CUDA support
        requires device with capability > (8, 0) but your GPU has capability (7, 5) (too old)
        operator wasn't built - see `python -m xformers.info` for more info
    `tritonflashattF` is not supported because:
        xFormers wasn't build with CUDA support
        requires device with capability > (8, 0) but your GPU has capability (7, 5) (too old)
        operator wasn't built - see `python -m xformers.info` for more info
        triton is not available
        requires GPU with sm80 minimum compute capacity, e.g., A100/H100/L4
        Only work on pre-MLIR triton for now
    `cutlassF` is not supported because:
        xFormers wasn't build with CUDA support
        operator wasn't built - see `python -m xformers.info` for more info
    `smallkF` is not supported because:
        max(query.shape[-1] != value.shape[-1]) > 32
        xFormers wasn't build with CUDA support
        dtype=torch.float16 (supported: {torch.float32})
        operator wasn't built - see `python -m xformers.info` for more info
        unsupported embed per head: 40
```


### Additional information

_No response_