[x] The issue exists after disabling all extensions
[ ] The issue exists on a clean installation of webui
[ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
[ ] The issue exists in the current version of the webui
[ ] The issue has not been reported before recently
[x] The issue has been reported before but has not been fixed yet
What happened?
Something's broken in webui-user. I tried to roll back the stable diff version to the old version 1.8.0. by rewriting the git command. Didn't work. Now the program stopped generating images. The problem is definitely not in the computer. But the error appears. In git pull origin master I wrote the command git reset --hard v1.8.0 and everything broke for me.
Tell me, has anyone figured out how to fix this error?
Steps to reproduce the problem
NotImplementedError: No operator found for memory_efficient_attention_forward with inputs: query : shape=(2, 4096, 8, 40) (torch.float16) key : shape=(2, 4096, 8, 40) (torch.float16) value : shape=(2, 4096, 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 operator wasn't built - see python -m xformers.info for more info tritonflashattF is not supported because: xFormers wasn't build with CUDA support operator wasn't built - see python -m xformers.info for more info triton is not available 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
What should have happened?
Tried to roll back the program to the correct version. It made it even worse.
What browsers do you use to access the UI ?
No response
Sysinfo
No.
Console logs
venv "venv\Scripts\Python.exe"
fatal: No names found, cannot describe anything.
Python 3.10.9 (tags/v3.10.9:1dd9be6, Dec 6 2022, 20:01:21) [MSC v.1934 64 bit (AMD64)]
Version: 1.8.0-RC
Commit hash: bef51aed032c0aaa5cfd80445bc4cf0d85b408b5
Launching Web UI with arguments: --xformers --autolaunch --theme dark
WARNING:xformers:WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:
PyTorch 2.1.2+cu121 with CUDA 1201 (you have 2.0.1+cu118)
Python 3.10.11 (you have 3.10.9)
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
==============================================================================
You are running torch 2.0.1+cu118.
The program is tested to work with torch 2.1.2.
To reinstall the desired version, run with commandline flag --reinstall-torch.
Beware that this will cause a lot of large files to be downloaded, as well as
there are reports of issues with training tab on the latest version.
Use --skip-version-check commandline argument to disable this check.
==============================================================================
[-] ADetailer initialized. version: 24.3.1, num models: 10
ControlNet preprocessor location: D:\SDP\stable-diffusion-portable-main\extensions\sd-webui-controlnet\annotator\downloads
2024-04-14 23:22:40,873 - ControlNet - INFO - ControlNet v1.1.441
2024-04-14 23:22:40,952 - ControlNet - INFO - ControlNet v1.1.441
Loading weights [bfb82d76c7] from D:\SDP\stable-diffusion-portable-main\models\Stable-diffusion\949bb26a4c989cbf387d10c62c6e0fac.safetensors
[LyCORIS]-WARNING: LyCORIS legacy extension is now loaded, if you don't expext to see this message, please disable this extension.
2024-04-14 23:22:41,249 - ControlNet - INFO - ControlNet UI callback registered.
*** Error executing callback ui_tabs_callback for D:\SDP\stable-diffusion-portable-main\extensions\sd-webui-depth-lib\scripts\main.py
Traceback (most recent call last):
File "D:\SDP\stable-diffusion-portable-main\modules\script_callbacks.py", line 180, in ui_tabs_callback
res += c.callback() or []
File "D:\SDP\stable-diffusion-portable-main\extensions\sd-webui-depth-lib\scripts\main.py", line 47, in on_ui_tabs dataset = gr.Examples(examples=os.path.join(maps_path, t), inputs=[png_input_area],examples_per_page=24,label="Depth Maps", elem_id="examples")
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio\helpers.py", line 58, in create_examples examples_obj = Examples(
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio\helpers.py", line 209, in __init__
self.processed_examples = [
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio\helpers.py", line 210, in <listcomp>
[
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio\helpers.py", line 211, in <listcomp>
component.postprocess(sample)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio\components\image.py", line 318, in postprocess
return client_utils.encode_url_or_file_to_base64(y)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio_client\utils.py", line 387, in encode_url_or_file_to_base64
return encode_file_to_base64(path)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\gradio_client\utils.py", line 360, in encode_file_to_base64
with open(f, "rb") as file:
PermissionError: [Errno 13] Permission denied: 'tmp'
---
Creating model from config: D:\SDP\stable-diffusion-portable-main\configs\v1-inference.yaml
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.
Startup time: 10.4s (prepare environment: 2.1s, import torch: 2.7s, import gradio: 0.8s, setup paths: 0.7s, initialize shared: 0.2s, other imports: 0.4s, load scripts: 2.6s, create ui: 0.4s, gradio launch: 0.4s).
Loading VAE weights specified in settings: D:\SDP\stable-diffusion-portable-main\models\VAE\vae-ft-ema-560000-ema-pruned.safetensors
Applying attention optimization: xformers... done.
Model loaded in 4.5s (load weights from disk: 0.4s, create model: 0.5s, apply weights to model: 1.6s, load VAE: 1.0s, calculate empty prompt: 0.8s).
0%| | 0/20 [00:00<?, ?it/s]
*** Error completing request
*** Arguments: ('task(bcn55hk1gljk7yp)', <gradio.routes.Request object at 0x000001F1B68AF6A0>, 'dog', '(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation', [], 20, 'Euler a', 1, 1, 8, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], 0, False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, {'ad_model': 'face_yolov8n.pt', 'ad_model_classes': '', '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': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, {'ad_model': 'None', 'ad_model_classes': '', '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': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, False, '', 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', inpaint_crop_input_image=False, hr_option='Both', save_detected_map=True, advanced_weighting=None), 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', inpaint_crop_input_image=False, hr_option='Both', save_detected_map=True, advanced_weighting=None), False, True, 3, 4, 0.15, 0.3, 'bicubic', 0.5, 2, True, False, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False, None, None, False, None, None, False, 50) {}
Traceback (most recent call last):
File "D:\SDP\stable-diffusion-portable-main\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "D:\SDP\stable-diffusion-portable-main\modules\call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\modules\txt2img.py", line 110, in txt2img
processed = processing.process_images(p)
File "D:\SDP\stable-diffusion-portable-main\modules\processing.py", line 785, in process_images
res = process_images_inner(p)
File "D:\SDP\stable-diffusion-portable-main\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 59, in processing_process_images_hijack
return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\modules\processing.py", line 921, 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 "D:\SDP\stable-diffusion-portable-main\modules\processing.py", line 1257, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "D:\SDP\stable-diffusion-portable-main\modules\sd_samplers_kdiffusion.py", line 234, 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 "D:\SDP\stable-diffusion-portable-main\modules\sd_samplers_common.py", line 261, in launch_sampling
return func()
File "D:\SDP\stable-diffusion-portable-main\modules\sd_samplers_kdiffusion.py", line 234, 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 "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\modules\sd_samplers_cfg_denoiser.py", line 237, in forward
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\modules\sd_hijack_utils.py", line 18, in <lambda>
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "D:\SDP\stable-diffusion-portable-main\modules\sd_hijack_utils.py", line 32, in __call__
return self.__orig_func(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
out = self.diffusion_model(x, t, context=cc)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\modules\sd_unet.py", line 91, in UNetModel_forward
return original_forward(self, x, timesteps, context, *args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 797, in forward
h = module(h, emb, context)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
x = layer(x, context)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 334, in forward
x = block(x, context=context[i])
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 269, in forward
return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 121, in checkpoint
return CheckpointFunction.apply(func, len(inputs), *args)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\autograd\function.py", line 506, in apply return super().apply(*args, **kwargs) # type: ignore[misc]
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 136, in forward
output_tensors = ctx.run_function(*ctx.input_tensors)
File "D:\SDP\stable-diffusion-portable-main\repositories\stable-diffusion-stability-ai\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 "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\SDP\stable-diffusion-portable-main\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 "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\xformers\ops\fmha\__init__.py", line 223, in memory_efficient_attention
return _memory_efficient_attention(
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\xformers\ops\fmha\__init__.py", line 321, in _memory_efficient_attention
return _memory_efficient_attention_forward(
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\xformers\ops\fmha\__init__.py", line 337, in _memory_efficient_attention_forward
op = _dispatch_fw(inp, False)
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-packages\xformers\ops\fmha\dispatch.py", line 120, in _dispatch_fw
return _run_priority_list(
File "D:\SDP\stable-diffusion-portable-main\venv\lib\site-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=(2, 4096, 8, 40) (torch.float16)
key : shape=(2, 4096, 8, 40) (torch.float16)
value : shape=(2, 4096, 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
operator wasn't built - see `python -m xformers.info` for more info
`tritonflashattF` is not supported because:
xFormers wasn't build with CUDA support
operator wasn't built - see `python -m xformers.info` for more info
triton is not available
`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
Everything was working fine just yesterday. Today the version has been updated. I don't know how to rollback. Only made things worse.
Checklist
What happened?
Something's broken in webui-user. I tried to roll back the stable diff version to the old version 1.8.0. by rewriting the git command. Didn't work. Now the program stopped generating images. The problem is definitely not in the computer. But the error appears. In git pull origin master I wrote the command git reset --hard v1.8.0 and everything broke for me. Tell me, has anyone figured out how to fix this error?
Steps to reproduce the problem
NotImplementedError: No operator found for
memory_efficient_attention_forward
with inputs: query : shape=(2, 4096, 8, 40) (torch.float16) key : shape=(2, 4096, 8, 40) (torch.float16) value : shape=(2, 4096, 8, 40) (torch.float16) attn_bias : <class 'NoneType'> p : 0.0decoderF
is not supported because: xFormers wasn't build with CUDA support attn_bias type is <class 'NoneType'> operator wasn't built - seepython -m xformers.info
for more infoflshattF@0.0.0
is not supported because: xFormers wasn't build with CUDA support operator wasn't built - seepython -m xformers.info
for more infotritonflashattF
is not supported because: xFormers wasn't build with CUDA support operator wasn't built - seepython -m xformers.info
for more info triton is not availablecutlassF
is not supported because: xFormers wasn't build with CUDA support operator wasn't built - seepython -m xformers.info
for more infosmallkF
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 - seepython -m xformers.info
for more info unsupported embed per head: 40What should have happened?
Tried to roll back the program to the correct version. It made it even worse.
What browsers do you use to access the UI ?
No response
Sysinfo
No.
Console logs
Additional information
Everything was working fine just yesterday. Today the version has been updated. I don't know how to rollback. Only made things worse.