Open n4mwd opened 7 months ago
hashFactory
commented
7 months ago I ran into the same issue.
I managed to get it working by running these two commands:
export USE_OPENVINO=1
pip install torch==2.1.0 torchvision==0.16.0I think the installation instructions need to be updated to reflect the latest commit 4400629
chenxiex
commented
6 months ago I ran into the same issue.
I managed to get it working by running these two commands:
export USE_OPENVINO=1 pip install torch==2.1.0 torchvision==0.16.0I think the installation instructions need to be updated to reflect the latest commit 4400629
I found this solution useful with python3.10.6. But python3.9 may still throw errors.
MorrisLu-Taipei
commented
5 months ago Thanks fo your all, finally it works now, A770 16G in WSL2 w/ubuntu 22.04 works fine BUT pretty slow 512*512 5 it/s takes 1min 48 sec -what I install sudo apt install libtcmalloc-minimal4 >> Cannot locate TCMalloc (improves CPU memory usage) pip install opencv-python-headless >> ImportError: libGL.so export USE_OPENVINO=1 pip install torch==2.1.0 torchvision==0.16.0
Is there an existing issue for this?
What happened?
There are numerous errors in the instructions for Linux install.
"list index out of range Traceback (most recent call last): File "/home/dennis/Downloads/stable-diffusion-webui/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 "/home/dennis/Downloads/stable-diffusion-webui/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"
Steps to reproduce the problem
On mx linux, open konsole and enter the commands below as given in the instructions: "# Make sure Python version is 3.10+ python3 -m venv sd_env source sd_env/bin/activate git clone https://github.com/openvinotoolkit/stable-diffusion-webui.git cd stable-diffusion-webui
export PYTORCH_TRACING_MODE=TORCHFX export COMMANDLINE_ARGS="--skip-torch-cuda-test --precision full --no-half"
Launch the WebUI
./webui.sh "
Once the UI opens in the web page, select openvino from the scripts menu.
Enter a prompt like "flower with a bee on it".
SD crashes.
What should have happened?
I think this bug is related to incorrect or incomplete instructions.
Sysinfo
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Speculative Store Bypass disabled via prctl", "Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization", "Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence", "Vulnerability Srbds: Not affected", "Vulnerability Tsx async abort: Not affected", "Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l2 invpcid_single cdp_l2 ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves split_lock_detect dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid movdiri movdir64b fsrm avx512_vp2intersect md_clear ibt flush_l1d arch_capabilities" ] }, "Exceptions": [ { "exception": "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 \"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/diffusers/models/resnet.py\", line 691, in forward\n hidden_states = self.norm1(hidden_states)\n'}\n\nWhile executing %self_norm1 : [#users=1] = call_module[target=self_norm1](args = (%input_tensor,), kwargs = {})\nOriginal traceback:\n File \"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/diffusers/models/resnet.py\", line 691, in forward\n hidden_states = self.norm1(hidden_states)\n\n\nSet torch._dynamo.config.verbose=True for more information\n\n\nYou can suppress this exception and fall back to eager by setting:\n torch._dynamo.config.suppress_errors = True\n", "traceback": [ [ "/home/dennis/Downloads/stable-diffusion-webui/stable-diffusion-webui/modules/call_queue.py, line 57, f", "res = list(func(*args, kwargs))" ], [ "/home/dennis/Downloads/stable-diffusion-webui/stable-diffusion-webui/modules/call_queue.py, line 36, f", "res = func(*args, *kwargs)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/stable-diffusion-webui/modules/txt2img.py, line 52, txt2img", "processed = modules.scripts.scripts_txt2img.run(p, args)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/stable-diffusion-webui/modules/scripts.py, line 601, run", "processed = script.run(p, script_args)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/stable-diffusion-webui/scripts/openvino_accelerate.py, line 1228, 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)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/stable-diffusion-webui/scripts/openvino_accelerate.py, line 979, process_images_openvino", "output = shared.sd_diffusers_model(" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/utils/_contextlib.py, line 115, decorate_context", "return func(args, kwargs)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py, line 840, call", "noise_pred = self.unet(" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/nn/modules/module.py, line 1501, _call_impl", "return forward_call(*args, kwargs)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py, line 82, forward", "return self.dynamo_ctx(self._orig_mod.forward)(*args, *kwargs)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py, line 209, _fn", "return fn(args, kwargs)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/diffusers/models/unet_2d_condition.py, line 932, forward", "emb = self.time_embedding(t_emb, timestep_cond)" ], [ "/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/diffusers/models/unet_2d_condition.py, line 1066,",
"sample, res_samples = downsample_block("
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/nn/modules/module.py, line 1501, _call_impl",
"return forward_call(*args, kwargs)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/diffusers/models/unet_2d_blocks.py, line 1159, forward",
"hidden_states = resnet(hidden_states, temb, scale=lora_scale)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/nn/modules/module.py, line 1501, _call_impl",
"return forward_call(*args, *kwargs)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/eval_frame.py, line 337, catch_errors",
"return callback(frame, cache_size, hooks)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py, line 404, _convert_frame",
"result = inner_convert(frame, cache_size, hooks)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py, line 104, _fn",
"return fn(args, kwargs)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py, line 262, _convert_frame_assert",
"return _compile("
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/utils.py, line 163, time_wrapper",
"r = func(*args, *kwargs)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py, line 324, _compile",
"out_code = transform_code_object(code, transform)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/bytecode_transformation.py, line 445, transform_code_object",
"transformations(instructions, code_options)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/convert_frame.py, line 311, transform",
"tracer.run()"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py, line 1726, run",
"super().run()"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py, line 576, run",
"and self.step()"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py, line 540, step",
"getattr(self, inst.opname)(inst)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/symbolic_convert.py, line 372, wrapper",
"self.output.compile_subgraph(self, reason=reason)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/output_graph.py, line 541, compile_subgraph",
"self.compile_and_call_fx_graph(tx, pass2.graph_output_vars(), root)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/output_graph.py, line 588, compile_and_call_fx_graph",
"compiled_fn = self.call_user_compiler(gm)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/utils.py, line 163, time_wrapper",
"r = func(args, *kwargs)"
],
[
"/home/dennis/Downloads/stable-diffusion-webui/sd_env/lib/python3.9/site-packages/torch/_dynamo/output_graph.py, line 675, call_user_compiler",
"raise BackendCompilerFailed(self.compiler_fn, e) from e"
]
]
}
],
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"GIT": "git",
"GRADIO_ANALYTICS_ENABLED": "False"
},
"Config": {
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"samples_format": "png",
"samples_filename_pattern": "",
"save_images_add_number": true,
"grid_save": true,
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"grid_background_color": "#ffffff",
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"save_mask": false,
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"outdir_samples": "",
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],
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"sd_vae_explanation": "VAE is a neural network that transforms a standard RGB\nimage into latent space representation and back. Latent space representation is what stable diffusion is working on during sampling\n(i.e. when the progress bar is between empty and full). For txt2img, VAE is used to create a resulting image after the sampling is finished.\nFor img2img, VAE is used to process user's input image before the sampling, and to create an image after sampling.",
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],
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]
}
What browsers do you use to access the UI ?
No response
Console logs
Additional information
Something is incorrect in the install instructions. The program seems to install ok, but crashes as soon as you try to use it.