[Bug]: return op(*args, **kwargs) RuntimeError #413
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directml
DirectML related or specific issue
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This error is probably an out-of-memory. Check memory consumption. |
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Checklist
What happened?
The process is interrupted during the use of model inference for image.
Graphics card：Intel UHD
Steps to reproduce the problem
run the user.bat
What should have happened?
The process is interrupted during the use of model inference for image.
What browsers do you use to access the UI ?
Google Chrome
Sysinfo
{
"Platform": "Windows-10-10.0.19041-SP0",
"Python": "3.10.11",
"Version": "1.8.0-RC",
"Commit": "25a3b6cbeea8a07afd5e4594afc2f1c79f41ac1a",
"Script path": "C:\A启动器",
"Data path": "C:\A启动器",
"Extensions dir": "C:\A启动器\extensions",
"Checksum": "7c2934e3c179bb518dfe1924b3227f4e62a343abd418168eeda03fed90b58854",
"Commandline": [
"C:\A启动器\launch.py",
"--skip-torch-cuda-test",
"--use-directml",
"--medvram-sdxl",
"--theme",
"dark",
"--opt-sub-quad-attention",
"--precision",
"full",
"--upcast-sampling",
"--no-half-vae",
"--api",
"--autolaunch"
],
"Torch env info": {
"torch_version": "1.13.1+cu117",
"is_debug_build": "False",
"cuda_compiled_version": "11.7",
"gcc_version": null,
"clang_version": null,
"cmake_version": null,
"os": "Microsoft Windows 10 企业版",
"libc_version": "N/A",
"python_version": "3.10.11 | packaged by Anaconda, Inc. | (main, May 16 2023, 00:55:32) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)",
"python_platform": "Windows-10-10.0.19041-SP0",
"is_cuda_available": "False",
"cuda_runtime_version": null,
"cuda_module_loading": "N/A",
"nvidia_driver_version": null,
"nvidia_gpu_models": null,
"cudnn_version": null,
"pip_version": "pip3",
"pip_packages": [
"numpy==1.26.2",
"open-clip-torch==2.20.0",
"pytorch-lightning==1.9.4",
"torch==1.13.1+cu117",
"torch-directml==0.1.13.1.dev230413",
"torchdiffeq==0.2.3",
"torchmetrics==1.3.1",
"torchsde==0.2.6",
"torchvision==0.14.1+cu117"
],
"conda_packages": null,
"hip_compiled_version": "N/A",
"hip_runtime_version": "N/A",
"miopen_runtime_version": "N/A",
"caching_allocator_config": "",
"is_xnnpack_available": "True"
},
"Exceptions": [
{
"exception": "",
"traceback": [
[
"C:\A启动器\modules\call_queue.py, line 57, f",
"res = list(func(*args, **kwargs))"
],
[
"C:\A启动器\modules\call_queue.py, line 36, f",
"res = func(*args, **kwargs)"
],
[
"C:\A启动器\modules\txt2img.py, line 110, txt2img",
"processed = processing.process_images(p)"
],
[
"C:\A启动器\modules\processing.py, line 787, process_images",
"res = process_images_inner(p)"
],
[
"C:\A启动器\modules\processing.py, line 1015, process_images_inner",
"samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)"
],
[
"C:\A启动器\modules\processing.py, line 1351, sample",
"samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))"
],
[
"C:\A启动器\modules\sd_samplers_kdiffusion.py, line 239, sample",
"samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
],
[
"C:\A启动器\modules\sd_samplers_common.py, line 261, launch_sampling",
"return func()"
],
[
"C:\A启动器\modules\sd_samplers_kdiffusion.py, line 239, ",
"samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\autograd\grad_mode.py, line 27, decorate_context",
"return func(*args, **kwargs)"
],
[
"C:\A启动器\repositories\k-diffusion\k_diffusion\sampling.py, line 594, sample_dpmpp_2m",
"denoised = model(x, sigmas[i] * s_in, **extra_args)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\modules\sd_samplers_cfg_denoiser.py, line 237, forward",
"x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\repositories\k-diffusion\k_diffusion\external.py, line 112, forward",
"eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)"
],
[
"C:\A启动器\repositories\k-diffusion\k_diffusion\external.py, line 138, get_eps",
"return self.inner_model.apply_model(*args, **kwargs)"
],
[
"C:\A启动器\modules\sd_hijack_utils.py, line 18, ",
"setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))"
],
[
"C:\A启动器\modules\sd_hijack_utils.py, line 30, call",
"return self.__sub_func(self.__orig_func, *args, **kwargs)"
],
[
"C:\A启动器\modules\sd_hijack_unet.py, line 48, apply_model",
"return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py, line 858, apply_model",
"x_recon = self.model(x_noisy, t, **cond)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py, line 1335, forward",
"out = self.diffusion_model(x, t, context=cc)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\modules\sd_unet.py, line 91, UNetModel_forward",
"return original_forward(self, x, timesteps, context, *args, **kwargs)"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py, line 802, forward",
"h = module(h, emb, context)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py, line 82, forward",
"x = layer(x, emb)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py, line 249, forward",
"return checkpoint("
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py, line 121, checkpoint",
"return CheckpointFunction.apply(func, len(inputs), *args)"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py, line 136, forward",
"output_tensors = ctx.run_function(*ctx.input_tensors)"
],
[
"C:\A启动器\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py, line 262, _forward",
"h = self.in_layers(x)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\container.py, line 204, forward",
"input = module(input)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\module.py, line 1194, _call_impl",
"return forward_call(*input, **kwargs)"
],
[
"C:\A启动器\extensions-builtin\Lora\networks.py, line 515, network_Conv2d_forward",
"return originals.Conv2d_forward(self, input)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\conv.py, line 463, forward",
"return self._conv_forward(input, self.weight, self.bias)"
],
[
"C:\A启动器\.ext\lib\site-packages\torch\nn\modules\conv.py, line 459, _conv_forward",
"return F.conv2d(input, weight, bias, self.stride,"
],
[
"C:\A启动器\modules\dml\amp\autocast_mode.py, line 43, ",
"setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: forward(op, args, kwargs))"
],
[
"C:\A启动器\modules\dml\amp\autocast_mode.py, line 15, forward",
"return op(*args, **kwargs)"
]
]
}
],
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"free": "3GB"
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"Config": {
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Console logs
Additional information
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