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The issue exists on a clean installation of Fooocus
The issue exists in the current version of Fooocus
The issue has not been reported before recently
The issue has been reported before but has not been fixed yet
What happened?
everytime i try to generate images it either black screens or gives me this error
It keeps doing this everytime even though i have tried everything to fix it.
Steps to reproduce the problem
After any image generation
What should have happened?
it should generate the image
What browsers do you use to access Fooocus?
No response
Where are you running Fooocus?
Locally
What operating system are you using?
Windows 11
Console logs
D:\Softwares\Foocus>.\python_embeded\python.exe -s Fooocus\entry_with_update.py
Already up-to-date
Update succeeded.
[System ARGV] ['Fooocus\\entry_with_update.py']
Python 3.10.9 (tags/v3.10.9:1dd9be6, Dec 6 2022, 20:01:21) [MSC v.1934 64 bit (AMD64)]
Fooocus version: 2.5.5
[Cleanup] Attempting to delete content of temp dir C:\Users\user\AppData\Local\Temp\fooocus
[Cleanup] Cleanup successful
You do not have [juggernautXL_v8Rundiffusion.safetensors] but you have [juggernautXL_version6Rundiffusion.safetensors].
Fooocus will use [juggernautXL_version6Rundiffusion.safetensors] to avoid downloading new models, but you are not using the latest models.
Use --always-download-new-model to avoid fallback and always get new models.
Total VRAM 6144 MB, total RAM 16202 MB
Set vram state to: NORMAL_VRAM
Always offload VRAM
Device: cuda:0 NVIDIA GeForce RTX 3060 Laptop GPU : native
VAE dtype: torch.bfloat16
Using pytorch cross attention
Refiner unloaded.
Running on local URL: http://127.0.0.1:7866
To create a public link, set`share=True`in`launch()`.model_type EPSUNet ADM Dimension 2816IMPORTANT: You are using gradio version 3.41.2, however version 4.29.0 is available, please upgrade.--------Using pytorch attention in VAEWorking with z of shape (1, 4, 32, 32) = 4096 dimensions.Using pytorch attention in VAEextra {'cond_stage_model.clip_l.logit_scale', 'cond_stage_model.clip_l.text_projection'}left over keys: dict_keys(['cond_stage_model.clip_l.transformer.text_model.embeddings.position_ids'])Base model loaded: D:\Softwares\Foocus\Fooocus\models\checkpoints\juggernautXL_version6Rundiffusion.safetensorsVAE loaded: NoneRequest to load LoRAs [] for model [D:\Softwares\Foocus\Fooocus\models\checkpoints\juggernautXL_version6Rundiffusion.safetensors].Fooocus V2 Expansion: Vocab with 642 words.D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()return self.fget.__get__(instance, owner)()Fooocus Expansion engine loaded for cuda:0, use_fp16 = True.Requested to load SDXLClipModelRequested to load GPT2LMHeadModelLoading 2 new models[Fooocus Model Management] Moving model(s) has taken 0.89 secondsStarted worker with PID 9460App started successful. Use the app with http://127.0.0.1:7866/ or 127.0.0.1:7866[Parameters] Adaptive CFG = 7[Parameters] CLIP Skip = 2[Parameters] Sharpness = 2[Parameters] ControlNet Softness = 0.25[Parameters] ADM Scale = 1.5 : 0.8 : 0.3[Parameters] Seed = 5451640945650293619[Parameters] CFG = 4[Fooocus] Loading control models ...[Parameters] Sampler = dpmpp_2m_sde_gpu - karras[Parameters] Steps = 30 - 15[Fooocus] Initializing ...[Fooocus] Loading models ...Refiner unloaded.[Fooocus] Processing prompts ...[Fooocus] Preparing Fooocus text #1 ...[Prompt Expansion] two random people, glowing, magic, winning, detailed, highly scientific, intricate, elegant, sharp focus, beautiful light, determined, colorful, artistic, fine detail, iconic, imposing, epic, clear, crisp, color, relaxed, attractive, complex, enhanced, loving, symmetry, novel, cinematic, dramatic, background, illuminated, amazing, gorgeous, flowing, elaborate[Fooocus] Preparing Fooocus text #2 ...[Prompt Expansion] two random people, glowing, infinite, detailed, dramatic, vibrant colors, inspired, open artistic, creative, fair, adventurous, emotional, cinematic, cute, colorful, highly coherent, cool, trendy, iconic, awesome, surreal, best, winning, perfect composition, beautiful, epic, stunning, amazing detail, pretty background, very inspirational,, full color, professional[Fooocus] Encoding positive #1 ...[Fooocus Model Management] Moving model(s) has taken 0.26 seconds[Fooocus] Encoding positive #2 ...[Fooocus] Encoding negative #1 ...[Fooocus] Encoding negative #2 ...[Parameters] Denoising Strength = 1.0[Parameters] Initial Latent shape: Image Space (896, 1152)Preparation time: 6.64 secondsUsing karras scheduler.[Fooocus] Preparing task 1/2 ...[Sampler] refiner_swap_method = joint[Sampler] sigma_min = 0.0291671771556139, sigma_max = 14.614643096923828Requested to load SDXLLoading 1 new modelloading in lowvram mode 3120.7200269699097[Fooocus Model Management] Moving model(s) has taken 4.84 seconds 7%|█████▌ | 2/30 [00:07<01:48, 3.88s/it]Traceback (most recent call last): File "D:\Softwares\Foocus\Fooocus\modules\async_worker.py", line 1471, in worker handler(task) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\modules\async_worker.py", line 1286, in handler imgs, img_paths, current_progress = process_task(all_steps, async_task, callback, controlnet_canny_path, File "D:\Softwares\Foocus\Fooocus\modules\async_worker.py", line 295, in process_task imgs = pipeline.process_diffusion( File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\modules\default_pipeline.py", line 379, in process_diffusion sampled_latent = core.ksampler( File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\modules\core.py", line 310, in ksampler samples = ldm_patched.modules.sample.sample(model, File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\sample.py", line 100, in sample samples = sampler.sample(noise, positive_copy, negative_copy, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\samplers.py", line 712, in samplereturn sample(self.model, noise, positive, negative, cfg, self.device, sampler, sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\modules\sample_hijack.py", line 158, in sample_hacked samples = sampler.sample(model_wrap, sigmas, extra_args, callback_wrap, noise, latent_image, denoise_mask, disable_pbar) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\samplers.py", line 557, in sample samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\k_diffusion\sampling.py", line 701, in sample_dpmpp_2m_sde_gpureturn sample_dpmpp_2m_sde(model, x, sigmas, extra_args=extra_args, callback=callback, disable=disable, eta=eta, s_noise=s_noise, noise_sampler=noise_sampler, solver_type=solver_type) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_contextreturn func(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\k_diffusion\sampling.py", line 613, in sample_dpmpp_2m_sde denoised = model(x, sigmas[i] * s_in, **extra_args) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\modules\patch.py", line 321, in patched_KSamplerX0Inpaint_forward out = self.inner_model(x, sigma, File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\samplers.py", line 271, in forwardreturn self.apply_model(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\samplers.py", line 268, in apply_model out = sampling_function(self.inner_model, x, timestep, uncond, cond, cond_scale, model_options=model_options, seed=seed) File "D:\Softwares\Foocus\Fooocus\modules\patch.py", line 237, in patched_sampling_function positive_x0, negative_x0 = calc_cond_uncond_batch(model, cond, uncond, x, timestep, model_options) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\samplers.py", line 222, in calc_cond_uncond_batch output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\model_base.py", line 85, in apply_model model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float() File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\modules\patch.py", line 437, in patched_unet_forward h = forward_timestep_embed(module, h, emb, context, transformer_options, output_shape, time_context=time_context, num_video_frames=num_video_frames, image_only_indicator=image_only_indicator) File "D:\Softwares\Foocus\Fooocus\ldm_patched\ldm\modules\diffusionmodules\openaimodel.py", line 43, in forward_timestep_embed x = layer(x, context, transformer_options) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\ldm\modules\attention.py", line 613, in forward x = block(x, context=context[i], transformer_options=transformer_options) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\ldm\modules\attention.py", line 440, in forwardreturn checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint) File "D:\Softwares\Foocus\Fooocus\ldm_patched\ldm\modules\diffusionmodules\util.py", line 189, in checkpointreturn func(*inputs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\ldm\modules\attention.py", line 500, in _forward n = self.attn1(n, context=context_attn1, value=value_attn1) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\ldm\modules\attention.py", line 395, in forwardreturn self.to_out(out) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\container.py", line 215, in forward input = module(input) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_implreturn self._call_impl(*args, **kwargs) File "D:\Softwares\Foocus\python_embeded\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_implreturn forward_call(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\ops.py", line 25, in forwardreturn self.forward_ldm_patched_cast_weights(*args, **kwargs) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\ops.py", line 20, in forward_ldm_patched_cast_weights weight, bias = cast_bias_weight(self, input) File "D:\Softwares\Foocus\Fooocus\ldm_patched\modules\ops.py", line 9, in cast_bias_weight weight = s.weight.to(device=input.device, dtype=input.dtype, non_blocking=non_blocking)RuntimeError: CUDA error: an illegal memory access was encounteredCUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.For debugging consider passing CUDA_LAUNCH_BLOCKING=1.Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.Total time: 34.98 seconds
Additional information
i dont think it did that before fooocus 2.5.5
The text was updated successfully, but these errors were encountered:
after a few days, the same issue came back. any help on permanent fix ?
but with this error this time RuntimeWarning: invalid value encountered in cast x_sample = x_sample.cpu().numpy().clip(0, 255).astype(np.uint8)
Checklist
What happened?
everytime i try to generate images it either black screens or gives me this error
It keeps doing this everytime even though i have tried everything to fix it.
Steps to reproduce the problem
After any image generation
What should have happened?
it should generate the image
What browsers do you use to access Fooocus?
No response
Where are you running Fooocus?
Locally
What operating system are you using?
Windows 11
Console logs
Additional information
i dont think it did that before fooocus 2.5.5
The text was updated successfully, but these errors were encountered: