[X] 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
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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: 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
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
---
Is there an existing issue for this?
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
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: 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=Trueinlaunch(). 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 rangeDuring 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
What browsers do you use to access the UI ?
Google Chrome
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