Giters

openvinotoolkit / stable-diffusion-webui

Stable Diffusion web UI

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

[Bug]: Use gpu to accelerate error reporting

lzk821 opened this issue · comments

commented

Is there an existing issue for this?

  • I have searched the existing issues and checked the recent builds/commits

What happened?

BackendCompilerFailed: openvino_fx raised RuntimeError: ShapeProp error for: node=%self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {}) with meta={'nn_module_stack': {'self_norm1': <class 'torch.nn.modules.normalization.GroupNorm'>}, 'stack_trace': ' File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\resnet.py", line 691, in forward\n hidden_states = self.norm1(hidden_states)\n'} While executing %self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {}) Original traceback: File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\resnet.py", line 691, in forward hidden_states = self.norm1(hidden_states) Set torch._dynamo.config.verbose=True for more information You can suppress this exception and fall back to eager by setting: torch._dynamo.config.suppress_errors = True
Time taken: 6.5 sec.

Steps to reproduce the problem

  1. Go to ....
  2. Press ....
  3. ...

What should have happened?

Pictures can be produced normally

Sysinfo

venv "D:\system\Documents\SD\stable-diffusion-webui\venv\Scripts\Python.exe"
fatal: No names found, cannot describe anything.
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: 1.6.0
Commit hash: 4400629
Launching Web UI with arguments: --skip-torch-cuda-test --precision full --no-half
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
Warning: caught exception 'Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx', memory monitor disabled
Loading weights [6ce0161689] from D:\system\Documents\SD\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors
Running on local URL: http://127.0.0.1:7860

To create a public link, set share=True in launch().
Creating model from config: D:\system\Documents\SD\stable-diffusion-webui\configs\v1-inference.yaml
Startup time: 10.6s (prepare environment: 0.4s, import torch: 3.6s, import gradio: 1.1s, setup paths: 1.0s, initialize shared: 0.5s, other imports: 0.7s, setup codeformer: 0.1s, load scripts: 2.4s, create ui: 0.4s, gradio launch: 0.4s).
Applying attention optimization: InvokeAI... done.
Model loaded in 3.5s (load weights from disk: 0.6s, create model: 0.3s, apply weights to model: 2.4s, calculate empty prompt: 0.1s).
{}
Loading weights [6ce0161689] from D:\system\Documents\SD\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors
OpenVINO Script: created model from config : D:\system\Documents\SD\stable-diffusion-webui\configs\v1-inference.yaml
0%| | 0/20 [00:00<?, ?it/s][2023-12-09 18:52:21,913] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,260] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,295] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,326] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,504] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,562] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,601] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,821] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,858] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py <function Conv2d.forward at 0x000001EF7F8DD900> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:23,059] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:23,115] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
list index out of range
Traceback (most recent call last):
File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 200, in openvino_fx
compiled_model = openvino_compile_cached_model(maybe_fs_cached_name, *example_inputs)
File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 426, in openvino_compile_cached_model
om.inputs[idx].get_node().set_element_type(dtype_mapping[input_data.dtype])
IndexError: list index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 147, in run_node
result = super().run_node(n)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 177, in run_node
return getattr(self, n.op)(n.target, args, kwargs)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 294, in call_module
return submod(*args, **kwargs)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\system\Documents\SD\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 459, in network_GroupNorm_forward
return originals.GroupNorm_forward(self, input)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\normalization.py", line 273, in forward
return F.group_norm(
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2526, in group_norm
return handle_torch_function(group_norm, (input, weight, bias,), input, num_groups, weight=weight, bias=bias, eps=eps)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\overrides.py", line 1534, in handle_torch_function
result = mode.torch_function(public_api, types, args, kwargs)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch_inductor\overrides.py", line 38, in torch_function
return func(*args, **kwargs)
File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2530, in group_norm
return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: Expected weight to be a vector of size equal to the number of channels in input, but got weight of shape [320] and input of shape [2, 1280]
0%| | 0/20 [00:01<?, ?it/s]
*** Error completing request
*** Arguments: ('task(av52dfc5c5rmdah)', 'tree', '', [], 20, 'DPM++ 2M Karras', 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x000001EF3F382B00>, 1, False, '', 0.8, -1, False, -1, 0, 0, 0, 'None', 'None', 'CPU', True, 'Euler a', True, False, 'None', 0.8, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False) {}
Traceback (most recent call last):
File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 200, in openvino_fx
compiled_model = openvino_compile_cached_model(maybe_fs_cached_name, *example_inputs)
File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 426, in openvino_compile_cached_model
om.inputs[idx].get_node().set_element_type(dtype_mapping[input_data.dtype])
IndexError: list index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 147, in run_node
    result = super().run_node(n)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 177, in run_node
    return getattr(self, n.op)(n.target, args, kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 294, in call_module
    return submod(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 459, in network_GroupNorm_forward
    return originals.GroupNorm_forward(self, input)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\normalization.py", line 273, in forward
    return F.group_norm(
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2526, in group_norm
    return handle_torch_function(group_norm, (input, weight, bias,), input, num_groups, weight=weight, bias=bias, eps=eps)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\overrides.py", line 1534, in handle_torch_function
    result = mode.__torch_function__(public_api, types, args, kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\overrides.py", line 38, in __torch_function__
    return func(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2530, in group_norm
    return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: Expected weight to be a vector of size equal to the number of channels in input, but got weight of shape [320] and input of shape [2, 1280]

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 670, in call_user_compiler
    compiled_fn = compiler_fn(gm, self.fake_example_inputs())
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\debug_utils.py", line 1055, in debug_wrapper
    compiled_gm = compiler_fn(gm, example_inputs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\backends\common.py", line 107, in wrapper
    return fn(model, inputs, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 233, in openvino_fx
    return compile_fx(subgraph, example_inputs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\compile_fx.py", line 415, in compile_fx
    model_ = overrides.fuse_fx(model_, example_inputs_)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\overrides.py", line 96, in fuse_fx
    gm = mkldnn_fuse_fx(gm, example_inputs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\mkldnn.py", line 509, in mkldnn_fuse_fx
    ShapeProp(gm, fake_mode=fake_mode).propagate(*example_inputs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 185, in propagate
    return super().run(*args)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 136, in run
    self.env[node] = self.run_node(node)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 152, in run_node
    raise RuntimeError(
RuntimeError: ShapeProp error for: node=%self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {}) with meta={'nn_module_stack': {'self_norm1': <class 'torch.nn.modules.normalization.GroupNorm'>}, 'stack_trace': '  File "D:\\system\\Documents\\SD\\stable-diffusion-webui\\venv\\lib\\site-packages\\diffusers\\models\\resnet.py", line 691, in forward\n    hidden_states = self.norm1(hidden_states)\n'}

While executing %self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {})
Original traceback:
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\resnet.py", line 691, in forward
    hidden_states = self.norm1(hidden_states)


The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "D:\system\Documents\SD\stable-diffusion-webui\modules\call_queue.py", line 57, in f
    res = list(func(*args, **kwargs))
  File "D:\system\Documents\SD\stable-diffusion-webui\modules\call_queue.py", line 36, in f
    res = func(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\modules\txt2img.py", line 52, in txt2img
    processed = modules.scripts.scripts_txt2img.run(p, *args)
  File "D:\system\Documents\SD\stable-diffusion-webui\modules\scripts.py", line 601, in run
    processed = script.run(p, *script_args)
  File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 1228, in run
    processed = process_images_openvino(p, model_config, vae_ckpt, p.sampler_name, enable_caching, openvino_device, mode, is_xl_ckpt, refiner_ckpt, refiner_frac)
  File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 979, in process_images_openvino
    output = shared.sd_diffusers_model(
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\pipelines\stable_diffusion\pipeline_stable_diffusion.py", line 840, in __call__
    noise_pred = self.unet(
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\eval_frame.py", line 82, in forward
    return self.dynamo_ctx(self._orig_mod.forward)(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\eval_frame.py", line 209, in _fn
    return fn(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\unet_2d_condition.py", line 924, in forward
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\unet_2d_condition.py", line 1066, in <graph break in forward>
    sample, res_samples = downsample_block(
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\unet_2d_blocks.py", line 1159, in forward
    hidden_states = resnet(hidden_states, temb, scale=lora_scale)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\eval_frame.py", line 337, in catch_errors
    return callback(frame, cache_size, hooks)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 404, in _convert_frame
    result = inner_convert(frame, cache_size, hooks)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 104, in _fn
    return fn(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 262, in _convert_frame_assert
    return _compile(
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\utils.py", line 163, in time_wrapper
    r = func(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 324, in _compile
    out_code = transform_code_object(code, transform)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\bytecode_transformation.py", line 445, in transform_code_object
    transformations(instructions, code_options)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 311, in transform
    tracer.run()
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 1726, in run
    super().run()
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 576, in run
    and self.step()
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 540, in step
    getattr(self, inst.opname)(inst)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 372, in wrapper
    self.output.compile_subgraph(self, reason=reason)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 541, in compile_subgraph
    self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 588, in compile_and_call_fx_graph
    compiled_fn = self.call_user_compiler(gm)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\utils.py", line 163, in time_wrapper
    r = func(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 675, in call_user_compiler
    raise BackendCompilerFailed(self.compiler_fn, e) from e
torch._dynamo.exc.BackendCompilerFailed: openvino_fx raised RuntimeError: ShapeProp error for: node=%self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {}) with meta={'nn_module_stack': {'self_norm1': <class 'torch.nn.modules.normalization.GroupNorm'>}, 'stack_trace': '  File "D:\\system\\Documents\\SD\\stable-diffusion-webui\\venv\\lib\\site-packages\\diffusers\\models\\resnet.py", line 691, in forward\n    hidden_states = self.norm1(hidden_states)\n'}

While executing %self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {})
Original traceback:
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\resnet.py", line 691, in forward
    hidden_states = self.norm1(hidden_states)


Set torch._dynamo.config.verbose=True for more information


You can suppress this exception and fall back to eager by setting:
    torch._dynamo.config.suppress_errors = True

What browsers do you use to access the UI ?

Google Chrome

Console logs

venv "D:\system\Documents\SD\stable-diffusion-webui\venv\Scripts\Python.exe"
fatal: No names found, cannot describe anything.
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug  1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: 1.6.0
Commit hash: 44006297e03a07f28505d54d6ba5fd55e0c1292d
Launching Web UI with arguments: --skip-torch-cuda-test --precision full --no-half
no module 'xformers'. Processing without...
no module 'xformers'. Processing without...
No module 'xformers'. Proceeding without it.
Warning: caught exception 'Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx', memory monitor disabled
Loading weights [6ce0161689] from D:\system\Documents\SD\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Creating model from config: D:\system\Documents\SD\stable-diffusion-webui\configs\v1-inference.yaml
Startup time: 10.6s (prepare environment: 0.4s, import torch: 3.6s, import gradio: 1.1s, setup paths: 1.0s, initialize shared: 0.5s, other imports: 0.7s, setup codeformer: 0.1s, load scripts: 2.4s, create ui: 0.4s, gradio launch: 0.4s).
Applying attention optimization: InvokeAI... done.
Model loaded in 3.5s (load weights from disk: 0.6s, create model: 0.3s, apply weights to model: 2.4s, calculate empty prompt: 0.1s).
{}
Loading weights [6ce0161689] from D:\system\Documents\SD\stable-diffusion-webui\models\Stable-diffusion\v1-5-pruned-emaonly.safetensors
OpenVINO Script:  created model from config : D:\system\Documents\SD\stable-diffusion-webui\configs\v1-inference.yaml
  0%|                                                                                           | 0/20 [00:00<?, ?it/s][2023-12-09 18:52:21,913] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,260] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,295] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,326] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,504] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,562] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,601] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,821] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:22,858] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py <function Conv2d.forward at 0x000001EF7F8DD900> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:23,059] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
[2023-12-09 18:52:23,115] torch._dynamo.symbolic_convert: [WARNING] D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\linear.py <function Linear.forward at 0x000001EF7F8DC280> [UserDefinedObjectVariable(LoraPatches), NNModuleVariable(), TensorVariable()] {} too many positional arguments
list index out of range
Traceback (most recent call last):
  File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 200, in openvino_fx
    compiled_model = openvino_compile_cached_model(maybe_fs_cached_name, *example_inputs)
  File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 426, in openvino_compile_cached_model
    om.inputs[idx].get_node().set_element_type(dtype_mapping[input_data.dtype])
IndexError: list index out of range

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 147, in run_node
    result = super().run_node(n)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 177, in run_node
    return getattr(self, n.op)(n.target, args, kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 294, in call_module
    return submod(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 459, in network_GroupNorm_forward
    return originals.GroupNorm_forward(self, input)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\normalization.py", line 273, in forward
    return F.group_norm(
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2526, in group_norm
    return handle_torch_function(group_norm, (input, weight, bias,), input, num_groups, weight=weight, bias=bias, eps=eps)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\overrides.py", line 1534, in handle_torch_function
    result = mode.__torch_function__(public_api, types, args, kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\overrides.py", line 38, in __torch_function__
    return func(*args, **kwargs)
  File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2530, in group_norm
    return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
RuntimeError: Expected weight to be a vector of size equal to the number of channels in input, but got weight of shape [320] and input of shape [2, 1280]
  0%|                                                                                           | 0/20 [00:01<?, ?it/s]
*** Error completing request
*** Arguments: ('task(av52dfc5c5rmdah)', 'tree', '', [], 20, 'DPM++ 2M Karras', 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x000001EF3F382B00>, 1, False, '', 0.8, -1, False, -1, 0, 0, 0, 'None', 'None', 'CPU', True, 'Euler a', True, False, 'None', 0.8, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False) {}
    Traceback (most recent call last):
      File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 200, in openvino_fx
        compiled_model = openvino_compile_cached_model(maybe_fs_cached_name, *example_inputs)
      File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 426, in openvino_compile_cached_model
        om.inputs[idx].get_node().set_element_type(dtype_mapping[input_data.dtype])
    IndexError: list index out of range

    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 147, in run_node
        result = super().run_node(n)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 177, in run_node
        return getattr(self, n.op)(n.target, args, kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 294, in call_module
        return submod(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 459, in network_GroupNorm_forward
        return originals.GroupNorm_forward(self, input)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\normalization.py", line 273, in forward
        return F.group_norm(
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2526, in group_norm
        return handle_torch_function(group_norm, (input, weight, bias,), input, num_groups, weight=weight, bias=bias, eps=eps)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\overrides.py", line 1534, in handle_torch_function
        result = mode.__torch_function__(public_api, types, args, kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\overrides.py", line 38, in __torch_function__
        return func(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 2530, in group_norm
        return torch.group_norm(input, num_groups, weight, bias, eps, torch.backends.cudnn.enabled)
    RuntimeError: Expected weight to be a vector of size equal to the number of channels in input, but got weight of shape [320] and input of shape [2, 1280]

    The above exception was the direct cause of the following exception:

    Traceback (most recent call last):
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 670, in call_user_compiler
        compiled_fn = compiler_fn(gm, self.fake_example_inputs())
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\debug_utils.py", line 1055, in debug_wrapper
        compiled_gm = compiler_fn(gm, example_inputs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\backends\common.py", line 107, in wrapper
        return fn(model, inputs, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 233, in openvino_fx
        return compile_fx(subgraph, example_inputs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\compile_fx.py", line 415, in compile_fx
        model_ = overrides.fuse_fx(model_, example_inputs_)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\overrides.py", line 96, in fuse_fx
        gm = mkldnn_fuse_fx(gm, example_inputs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_inductor\mkldnn.py", line 509, in mkldnn_fuse_fx
        ShapeProp(gm, fake_mode=fake_mode).propagate(*example_inputs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 185, in propagate
        return super().run(*args)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\interpreter.py", line 136, in run
        self.env[node] = self.run_node(node)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\fx\passes\shape_prop.py", line 152, in run_node
        raise RuntimeError(
    RuntimeError: ShapeProp error for: node=%self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {}) with meta={'nn_module_stack': {'self_norm1': <class 'torch.nn.modules.normalization.GroupNorm'>}, 'stack_trace': '  File "D:\\system\\Documents\\SD\\stable-diffusion-webui\\venv\\lib\\site-packages\\diffusers\\models\\resnet.py", line 691, in forward\n    hidden_states = self.norm1(hidden_states)\n'}

    While executing %self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {})
    Original traceback:
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\resnet.py", line 691, in forward
        hidden_states = self.norm1(hidden_states)


    The above exception was the direct cause of the following exception:

    Traceback (most recent call last):
      File "D:\system\Documents\SD\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "D:\system\Documents\SD\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\modules\txt2img.py", line 52, in txt2img
        processed = modules.scripts.scripts_txt2img.run(p, *args)
      File "D:\system\Documents\SD\stable-diffusion-webui\modules\scripts.py", line 601, in run
        processed = script.run(p, *script_args)
      File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 1228, in run
        processed = process_images_openvino(p, model_config, vae_ckpt, p.sampler_name, enable_caching, openvino_device, mode, is_xl_ckpt, refiner_ckpt, refiner_frac)
      File "D:\system\Documents\SD\stable-diffusion-webui\scripts\openvino_accelerate.py", line 979, in process_images_openvino
        output = shared.sd_diffusers_model(
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\pipelines\stable_diffusion\pipeline_stable_diffusion.py", line 840, in __call__
        noise_pred = self.unet(
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\eval_frame.py", line 82, in forward
        return self.dynamo_ctx(self._orig_mod.forward)(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\eval_frame.py", line 209, in _fn
        return fn(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\unet_2d_condition.py", line 924, in forward
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\unet_2d_condition.py", line 1066, in <graph break in forward>
        sample, res_samples = downsample_block(
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\unet_2d_blocks.py", line 1159, in forward
        hidden_states = resnet(hidden_states, temb, scale=lora_scale)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\eval_frame.py", line 337, in catch_errors
        return callback(frame, cache_size, hooks)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 404, in _convert_frame
        result = inner_convert(frame, cache_size, hooks)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 104, in _fn
        return fn(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 262, in _convert_frame_assert
        return _compile(
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\utils.py", line 163, in time_wrapper
        r = func(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 324, in _compile
        out_code = transform_code_object(code, transform)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\bytecode_transformation.py", line 445, in transform_code_object
        transformations(instructions, code_options)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\convert_frame.py", line 311, in transform
        tracer.run()
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 1726, in run
        super().run()
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 576, in run
        and self.step()
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 540, in step
        getattr(self, inst.opname)(inst)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\symbolic_convert.py", line 372, in wrapper
        self.output.compile_subgraph(self, reason=reason)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 541, in compile_subgraph
        self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 588, in compile_and_call_fx_graph
        compiled_fn = self.call_user_compiler(gm)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\utils.py", line 163, in time_wrapper
        r = func(*args, **kwargs)
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\torch\_dynamo\output_graph.py", line 675, in call_user_compiler
        raise BackendCompilerFailed(self.compiler_fn, e) from e
    torch._dynamo.exc.BackendCompilerFailed: openvino_fx raised RuntimeError: ShapeProp error for: node=%self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {}) with meta={'nn_module_stack': {'self_norm1': <class 'torch.nn.modules.normalization.GroupNorm'>}, 'stack_trace': '  File "D:\\system\\Documents\\SD\\stable-diffusion-webui\\venv\\lib\\site-packages\\diffusers\\models\\resnet.py", line 691, in forward\n    hidden_states = self.norm1(hidden_states)\n'}

    While executing %self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {})
    Original traceback:
      File "D:\system\Documents\SD\stable-diffusion-webui\venv\lib\site-packages\diffusers\models\resnet.py", line 691, in forward
        hidden_states = self.norm1(hidden_states)


    Set torch._dynamo.config.verbose=True for more information


    You can suppress this exception and fall back to eager by setting:
        torch._dynamo.config.suppress_errors = True


---

Additional information

No response