Help for a Noob.

[rasiel21]

Hi! Maybe someone could help me. Everything was working and but I had the dumbest idea to try adding more models and as a result I Fu*** Up. I deleted everything and started from scratch but had no luck. I tried to find a similar problem trying not to bother but nothing I found helped. The error is:

Error completing request
Arguments: ('planet earth', '', 'None', 'None', 20, 0, False, False, 1, 1, 7, -1.0, -1.0, 0, 0, 0, False, 768, 768, False, 0.7, 2, 'Latent', 0, 0, 0, 0, False, False, False, False, '', 1, '', 0, '', True, False, False) {}
Traceback (most recent call last):
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\call_queue.py", line 45, in f
res = list(func(*args, **kwargs))
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\call_queue.py", line 28, in f
res = func(*args, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\txt2img.py", line 52, in txt2img
processed = process_images(p)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\processing.py", line 479, in process_images
res = process_images_inner(p)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\processing.py", line 608, in process_images_inner
samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\processing.py", line 797, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\sd_samplers.py", line 537, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\sd_samplers.py", line 440, in launch_sampling
return func()
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\sd_samplers.py", line 537, in
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\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\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\sd_samplers.py", line 338, in forward
x_out = self.inner_model(x_in, sigma_in, cond={"c_crossattn": [cond_in], "c_concat": [image_cond_in]})
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 167, in forward
return self.get_v(input * c_in, self.sigma_to_t(sigma), **kwargs) * c_out + input * c_skip
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 177, in get_v
return self.inner_model.apply_model(x, t, cond)
File "C:\Users\Viral\OneDrive\Documents\GitHub\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\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1329, in forward
out = self.diffusion_model(x, t, context=cc)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 781, in forward
h = module(h, emb, context)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 82, in forward
x = layer(x, emb)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\modules\sd_hijack_checkpoint.py", line 10, in ResBlock_forward
return checkpoint(self._forward, x, emb)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\utils\checkpoint.py", line 235, in checkpoint
return CheckpointFunction.apply(function, preserve, *args)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\utils\checkpoint.py", line 96, in forward
outputs = run_function(*args)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 262, in _forward
h = self.in_layers(x)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\container.py", line 139, in forward
input = module(input)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py", line 457, in forward
return self._conv_forward(input, self.weight, self.bias)
File "C:\Users\Viral\OneDrive\Documents\GitHub\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py", line 453, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR
You can try to repro this exception using the following code snippet. If that doesn't trigger the error, please include your original repro script when reporting this issue.

import torch
torch.backends.cuda.matmul.allow_tf32 = True
torch.backends.cudnn.benchmark = True
torch.backends.cudnn.deterministic = False
torch.backends.cudnn.allow_tf32 = True
data = torch.randn([2, 1280, 48, 48], dtype=torch.half, device='cuda', requires_grad=True)
net = torch.nn.Conv2d(1280, 640, kernel_size=[3, 3], padding=[1, 1], stride=[1, 1], dilation=[1, 1], groups=1)
net = net.cuda().half()
out = net(data)
out.backward(torch.randn_like(out))
torch.cuda.synchronize()

ConvolutionParams
memory_format = Contiguous
data_type = CUDNN_DATA_HALF
padding = [1, 1, 0]
stride = [1, 1, 0]
dilation = [1, 1, 0]
groups = 1
deterministic = false
allow_tf32 = true
input: TensorDescriptor 000002385058FDF0
type = CUDNN_DATA_HALF
nbDims = 4
dimA = 2, 1280, 48, 48,
strideA = 2949120, 2304, 48, 1,
output: TensorDescriptor 0000023850590020
type = CUDNN_DATA_HALF
nbDims = 4
dimA = 2, 640, 48, 48,
strideA = 1474560, 2304, 48, 1,
weight: FilterDescriptor 0000023856CEF110
type = CUDNN_DATA_HALF
tensor_format = CUDNN_TENSOR_NCHW
nbDims = 4
dimA = 640, 1280, 3, 3,
Pointer addresses:
input: 0000000C03080000
output: 0000000BA1000000
weight: 0000000B6B520000

[Cyberes]

Probably OOM.

[BetaDoggo]

It seems like you're running it out of a OneDrive directory. I'm not sure exactly how OneDrive directories work but I'd recommend moving your installation into a normal folder to see if that fixes the issue. This is definitely not an OOM as Cyberes suggests.

PS. I recommend the test prompt "Edward Snowden"

[Cyberes]

I need more information.

GPU model?
Cuda version?
Drivers up to date?
What settings are you using?
What launch args?
What are your parameters for generating?

[rasiel21]

I deleted the drivers and re-installed them again and the problem was solved thanks to your checklist. Thanks again for your help and for being so kind and warned me about the prompt. Some people are just stupid enough to suggest something harmful to others.

[mezotaken]

@rasiel21 it was a joke about the prompt

[rasiel21]

I'm sorry. I'm just a noob :)

[Cyberes]

Glad you got it figured out.

[rasiel21]

Hi again guys. Today my automatic1111 won't load. Sorry to bother you but if anyone could help, that would be great.
loading up it says press any key to continue and the windows closes.

#######################################################################################################

Launching Web UI with arguments: --no-half
No module 'xformers'. Proceeding without it.

You are running torch 1.12.1+cu113.
The program is tested to work with torch 1.13.1.
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.

SD-Webui API layer loaded
Loading weights [cac0a972cf] from E:\stable-diffusion-webui\models\Stable-diffusion\superhero-diffusion.ckpt
Creating model from config: E:\stable-diffusion-webui\configs\v1-inference.yaml
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
Applying cross attention optimization (Doggettx).
Textual inversion embeddings loaded(0):
Model loaded in 5.1s (load weights from disk: 0.9s, create model: 0.6s, apply weights to model: 0.8s, move model to device: 1.3s, load textual inversion embeddings: 1.5s).
Traceback (most recent call last):
File "E:\stable-diffusion-webui\launch.py", line 356, in
start()
File "E:\stable-diffusion-webui\launch.py", line 351, in start
webui.webui()
File "E:\stable-diffusion-webui\webui.py", line 243, in webui
shared.demo = modules.ui.create_ui()
File "E:\stable-diffusion-webui\modules\ui.py", line 448, in create_ui
with gr.Blocks(analytics_enabled=False) as txt2img_interface:
File "E:\stable-diffusion-webui\venv\lib\site-packages\gradio\blocks.py", line 548, in init
super().init(render=False, **kwargs)
File "E:\stable-diffusion-webui\modules\scripts.py", line 561, in BlockContext_init
add_classes_to_gradio_component(self)
File "E:\stable-diffusion-webui\modules\scripts.py", line 529, in add_classes_to_gradio_component
comp.elem_classes = ["gradio-" + comp.get_block_name(), *(comp.elem_classes or [])]
AttributeError: 'Blocks' object has no attribute 'elem_classes'
Press any key to continue . . .

[rasiel21]

Hi guys, yesterday everything was working perfectly but today i was greeted with a new error. I tried everything I found online to not bother anyone here but as you imagine, nothing worked for me. If someone could help, please let me know. Below is the error displayed at the bottom following by press any key to continue... and the window closes as soon as I hit any key. Thanks for your help.

ModuleNotFoundError: No module named 'huggingface_hub.utils._typing'
Press any key to continue . . .