stable-diffusion-webui
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Published
20 hours ago •
AUTOMATIC1111
AUTOMATIC1111
[Bug]: RuntimeError: CUDA error: an illegal memory access was encountered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
Is there an existing issue for this?
- [X] I have searched the existing issues and checked the recent builds/commits
What happened?
SD not generating image. Tried diferent combinations, installers, also reinstalled windows/drivers/pytorch the same way i did on other Machines, where SD works fine. for some reason SD has problems with the GPU.
Steps to reproduce the problem
Setup: GPU: RTX 2070 Super (8GB)
What should have happened?
Generate image
Version or Commit where the problem happens
v1.5.1
What Python version are you running on ?
Python 3.10.x
What platforms do you use to access the UI ?
Windows
What device are you running WebUI on?
Nvidia GPUs (RTX 20 above)
Cross attention optimization
InvokeAI
What browsers do you use to access the UI ?
Microsoft Edge
Command Line Arguments
--xformers --device-id 0 --no-half --opt-split-attention --opt-channelslast --opt-sdp-no-mem-attention --administrator --always-batch-cond-uncond --precision full
List of extensions
none
Console logs
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Loading A111 WebUI Launcher
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i Settings file found, loading
→ Updating Settings File ✓
i Launcher Version 1.7.0
i Found a custom WebUI Config
i No Launcher launch options
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→ Checking requirements :
i Python 3.10.6150.1013 found in registry: C:\Users\ai\AppData\Local\Programs\Python\Python310\
i Clearing PATH of any mention of Python
→ Adding python 3.10 to path ✓
i Git found and already in PATH: C:\Program Files\Git\cmd\git.exe
i Automatic1111 SD WebUI found: C:\Users\ai\Desktop\SD\stable-diffusion-webui
i One or more checkpoint models were found
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Loading Complete, opening launcher
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i Arguments are now: --device-id 0 --no-half --opt-split-attention --opt-channelslast --opt-sdp-no-mem-attention --administrator --always-batch-cond-uncond
i Enable Xformers updated to True
→ Updating Settings File ✓
i Arguments are now: --xformers --device-id 0 --no-half --opt-split-attention --opt-channelslast --opt-sdp-no-mem-attention --administrator --always-batch-cond-uncond
i Additional Args updated
→ Updating Settings File ✓
i Arguments are now: --xformers --device-id 0 --no-half --opt-split-attention --opt-channelslast --opt-sdp-no-mem-attention --administrator --always-batch-cond-uncond --precision full
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↺ Updating Webui
✓ Done
i There is no extension in the extensions folder
i Arguments are now: --xformers --device-id 0 --no-half --opt-split-attention --opt-channelslast --opt-sdp-no-mem-attention --administrator --always-batch-cond-uncond --precision full
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WEBUI LAUNCHING VIA EMS LAUNCHER, EXIT THIS WINDOW TO STOP THE WEBUI
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! Any error happening after 'commit hash : XXXX' is not related to the launcher. Please report them on Automatic1111's github instead :
☁ https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/new/choose
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Cancel
venv "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: v1.5.1
Commit hash: 68f336bd994bed5442ad95bad6b6ad5564a5409a
Launching Web UI with arguments: --autolaunch --xformers --device-id 0 --no-half --opt-split-attention --opt-channelslast --opt-sdp-no-mem-attention --administrator --always-batch-cond-uncond --precision full
Loading weights [27a4ac756c] from C:\Users\ai\Desktop\SD\stable-diffusion-webui\models\Stable-diffusion\SD15NewVAEpruned.ckpt
Running on local URL: http://127.0.0.1:7860
To create a public link, set `share=True` in `launch()`.
Startup time: 30.4s (launcher: 11.2s, import torch: 7.0s, import gradio: 2.9s, setup paths: 3.5s, other imports: 2.9s, setup codeformer: 0.1s, load scripts: 1.4s, create ui: 0.7s, gradio launch: 0.5s).
Creating model from config: C:\Users\ai\Desktop\SD\stable-diffusion-webui\configs\v1-inference.yaml
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
Applying attention optimization: Doggettx... done.
Model loaded in 34.5s (load weights from disk: 8.2s, create model: 17.8s, apply weights to model: 1.0s, apply channels_last: 0.9s, move model to device: 6.1s, calculate empty prompt: 0.3s).
0%| | 0/20 [00:01<?, ?it/s]Exception in thread MemMon:
Traceback (most recent call last):
File "C:\Users\ai\AppData\Local\Programs\Python\Python310\lib\threading.py", line 1016, in _bootstrap_inner
*** Error completing request
*** Arguments: ('task(623ht1rllkhdrvd)', 'forest, trees, sunny day', 'low quality, ugly, rainy', [], 20, 0, False, False, 1, 1, 7, -1.0, -1.0, 0, 0, 0, False, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 0, '', '', [], <gradio.routes.Request object at 0x00000224457C1D80>, 0, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0) {}
self.run()
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\memmon.py", line 53, in run
free, total = self.cuda_mem_get_info()
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\memmon.py", line 34, in cuda_mem_get_info
return torch.cuda.mem_get_info(index)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\cuda\memory.py", line 618, in mem_get_info
return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: CUDA error: an illegal memory access was encountered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
Traceback (most recent call last):
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\call_queue.py", line 58, in f
res = list(func(*args, **kwargs))
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\txt2img.py", line 62, in txt2img
processed = processing.process_images(p)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\processing.py", line 677, in process_images
res = process_images_inner(p)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\processing.py", line 794, 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 "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\processing.py", line 1054, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 464, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 303, in launch_sampling
return func()
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 464, in <lambda>
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 183, in forward
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\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 "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "C:\Users\ai\Desktop\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 "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in __call__
return self.__orig_func(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
out = self.diffusion_model(x, t, context=cc)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1538, in _call_impl
result = forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\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 "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 797, in forward
h = module(h, emb, context)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
x = layer(x, context)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 329, in forward
x = self.proj_in(x)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 376, in network_Conv2d_forward
return torch.nn.Conv2d_forward_before_network(self, input)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py", line 463, in forward
return self._conv_forward(input, self.weight, self.bias)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py", line 459, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: CUDA error: an illegal memory access was encountered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
---
Traceback (most recent call last):
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\gradio\routes.py", line 422, in run_predict
output = await app.get_blocks().process_api(
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1323, in process_api
result = await self.call_function(
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 1051, in call_function
prediction = await anyio.to_thread.run_sync(
File "C:\Users\ai\Desktop\SD\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 "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 877, in run_sync_in_worker_thread
return await future
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\anyio\_backends\_asyncio.py", line 807, in run
result = context.run(func, *args)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\call_queue.py", line 93, in f
mem_stats = {k: -(v//-(1024*1024)) for k, v in shared.mem_mon.stop().items()}
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\memmon.py", line 92, in stop
return self.read()
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\memmon.py", line 77, in read
free, total = self.cuda_mem_get_info()
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\modules\memmon.py", line 34, in cuda_mem_get_info
return torch.cuda.mem_get_info(index)
File "C:\Users\ai\Desktop\SD\stable-diffusion-webui\venv\lib\site-packages\torch\cuda\memory.py", line 618, in mem_get_info
return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: CUDA error: an illegal memory access was encountered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
Additional information
No response
Sometimes, this error happens because of OOM. Maybe you can solve it with a small batchsize or other ways to decrease the use of VRAM.
RuntimeError: CUDA error: an illegal memory access was encountered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
Same error on a RTX 4070 laptop and on a RTX2070 Desktop pc. + In the event viewer multiple nvlddmkm error event ID 13:
\Device\Video8 Graphics SM Warp Exception on (GPC 2, TPC 5, SM 1): Illegal Instruction Encoding
