Intel Arc Graphics Thread #476
Replies: 85 comments 249 replies
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UPDATE:
Before Intel update it, the code needs to be modified like this to avoid reporting errors: - match operation:
- case "multiply":
- output[top:bottom, left:right] = destination_portion * source_portion
- case "add":
- output[top:bottom, left:right] = destination_portion + source_portion
- case "subtract":
- output[top:bottom, left:right] = destination_portion - source_portion
+ if operation == "multiply":
+ output[top:bottom, left:right] = destination_portion * source_portion
+ elif operation == "add":
+ output[top:bottom, left:right] = destination_portion + source_portion
+ elif operation == "subtract":
+ output[top:bottom, left:right] = destination_portion - source_portionOf course not modifying it doesn't seem to affect normal usage. |
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I added this fix to master: 476d543 |
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About Karras scheduler: Currently using it causes a -996 "uses-fp64-math" error, which may be fixed in the next IPEX release (intel/intel-extension-for-pytorch#285) Until then, can specify to use # comfy/samplers.py
- sigmas = k_diffusion_sampling.get_sigmas_karras(n=steps, sigma_min=self.sigma_min, sigma_max=self.sigma_max, device=self.device)
+ sigmas = k_diffusion_sampling.get_sigmas_karras(n=steps, sigma_min=self.sigma_min, sigma_max=self.sigma_max, device="cpu") |
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is it Linux only or can you use this on a win10 machine? |
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You should be able to use WSL, but I haven't tested it. |
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So again, sharing the good news. An XPU version of their Pytorch extension with Pytorch 2.0 support,
Hats off to ComfyUI for being the only Stable Diffusion UI to be able to do it at the moment but there are a bunch of caveats with running Arc and Stable Diffusion right now from the research I have done. As of the time of posting: 1.) Setup can still be complicated in some respects and can randomly not work because Intel is only really verifying for enterprise Linux distributions and Ubuntu. My base Linux Fedora 38 install has the RPMs installed but I get a cryptic error regarding the runtime saying 2.) From what I have read at intel/intel-extension-for-pytorch#398, there is no native Windows version for some wheels to get 3.) Intel Arc right now has a huge problem with allocating more than 4GB of VRAM in IPEX even though the card has more VRAM in the case of the A750/A770 according to intel/intel-extension-for-pytorch#325. This seems to have mitigations elsewhere in Intel's oneAPI stack like their OpenCL compute runtime where anything you compile, you can work your code to go around the restriction via some flags and changed code according to intel/compute-runtime#627. No workarounds, it seems, until someone gets Intel to fix it. 4.) Because of that, experimenting with other Stable Diffusion UIs, it seems like every once in a while, Arc will occasionally run out of VRAM if you decide to not use lower VRAM flags and throw a 5.) Intel has an equivalent to I'm not even sure if I'm sure that Intel GPU support will not a big priority at the moment for the project, given the big blocker at this point is the 4GB VRAM limit which needs to be fixed by Intel. But that being said, things should be working a lot better than it is at the moment, maybe not average user ready, but should be ready for any mildly technical person. I really want to play with ComfyUI more but I really don't want to restart the application server for every several image I might want to generate even or rolling a dice for SDXL to actually finish a workflow. But the Arc cards are strong. I managed to equal the Nvidia RTX 3070 Ti in certain Stable Diffusion workflows with my 16 GB Intel Arc A770 so I look forward to the future when things are more mature and all the stars are aligned. Also not sure what issues need to be open here but there is potentially 2-3 of them that could be made from my report. Edit: Added a caveat I forgot to mention and filled in some information and fixed some typos. |
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Maybe it doesn't like the shifting from ram to vram, try running it with --highvram |
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That's really counterintuitive. But yeah, it works for single image generation, was able to generate 5 images in a row without crashing. It does still crash when I tried to enable a batch of 2 because I decided to push my luck and may still crash like the other UIs when IPEX decides to randomly stop working but maybe that is to be expected given what I mentioned above about VRAM allocation and etc. But yeah, I think that brings this from theoretically useful to possibly useful. I'll file the |
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@simonlui From what I found
Quote from the last link: |
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I followed you steps, only used the updated version and then I got this issue can you tell me whats wrong? |
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So this took me a bit of time, but I have the Docker image I used published here so hopefully someone can find it useful. Some things to note I've found while poking and experimenting with things. 1.) A lot of the issues are gone mentioned before by @kwaa months ago like the Karras scheduler not working, where it is working now even with the new dpmpp_3 schedulers, or noise issues if not using split attention which is gone for the most part unless your graphics driver has crashed too many times and a restart of the computer fixes that. Anyways, hope people have good success with it like I did. I might try and see why ipexrun is failing but for now, I am going to take a break. Edit: Added in a caveat I forgot to mention and fixed some typos. |
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In the event anyone else missed it: I seem to be missing the file that gets sourced from /opt/intel, too... may edit this post once I figure it out. |
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Because Arch only packages the basekit and disaggregates all the other toolkits into seperate components which is kinda confusing why. Also, opt/intel/oneapi/setvars.sh should be part of the basekit package as you can see here. You may need to do a reinstall of the basekit if you don't see the file. |
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I may update this guide in the near future. |
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Well, short story. After spend whole day to install Arch Linux on Windows 10 WSL (2 in my case). After all procedures, I stuck on
The installer reach a 87% and starts roll back all changes, because intel-oneapi-basekit not contain library libtbb.so.12 that needed to install oneAPI AI Analytics Toolkit v2023. The packgage that contains needed library is intel-oneapi-compiler-shared-runtime but it conflict with intel-oneapi-basekit. Because the istall procedure can't finish with intel-oneapi-basekit, I install intel-oneapi-compiler-shared-runtime. ComfyUI runs: [{user}@pc ArchLinux]$ But if i try to generate image I get an next error: As can see, I tries params like --force-fp16 --bf16-vae --lowvram --use-split-cross-attention --highvram but it's have no effect. So, models are loaded, but KSampler are crashes. And that's my dead end, because I have no idea what's going on. Not in ComfyUI itself, and also there more in Linux Arch. But I suppose this can be a kind of report. |
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Well, first off, there's no reason for you to use Arch Linux on WSL2 anyways, because you can pick Ubuntu and it's the only supported distribution that Intel supports for non-enterprise users anyways so using anything else is going to be painful and with WSL, it's a fool's errand because it won't gives you any additional benefits like speed and etc. like you may think it does. Secondly, that's what I made my Docker image for because it's very easy to mess up the install and there are a lot of chances to go wrong. Just on a cursory glance, you have the wrong package probably for TBB and the compiler runtime conflict is probably the issue. If you do want to fix the issue, you're going to have to reinstall everything correctly. |
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Doesn't work on Windows too, unfortunatelly. Do a step-by-step and get "missing startup.sh". Because this error is not specific, without code of error - kind of common for docker using - it's have no specific result in google. Fixing that case basing only on your tutorial not seems possible. |
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@roflosaur Sorry, it took a while to diagnose because I needed to set up a virtual machine to debug the issue you ran into but I found the root issue which was git was changing the line endings of the files based on OS where startup.sh needed to be tied to Unix line endings only. I have set up a .gitattributes to fix this. I would advise you to do a clean checkout again via deleting and cloning my repository again or if you know the command line, you can re-checkout the repository with the new .gitattributes applied. Thanks for reporting the issue. |
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Here is an error when build the app. I also downloaded and installed manually Intel One API Base Kit version 2023.1.0.47256 but useless. Can't build an app thus. |
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Welp, aren't you unlucky on your timing here? Intel has broken their GPG key for OneAPI repository and that means nothing from oneAPI can be downloaded from said repository. I unfortunately can't help you here since my image depends on downloading those packages fresh from Intel for updating reasons. So until they get their stuff together over there, you're stuck as am I. If you want to follow progress on when a fix might come, see this issue |
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I don't use Windows, but all the pieces should be together to run ComfyUI on Windows now without any horrible downsides like no AOT compilation or missing packages since a new unofficial Intel Extension for Python package has been released without needing any installation of external dependencies and bundling it all together. It remains to be seen whether there will ever be an official package that does this so this package is the best chance anyone has at actually using Arc on Windows natively. According to reports, it is a bit faster than WSL2 but slower than Linux native. The rough steps to do this should be roughly the same as the process outlined in the opening post for Linux minus platform-specific things. 1.) Make sure you install an Intel driver that is 4952 or newer. The latest driver can be found here python -m ensurepip --upgrade3.) Install git from here using the GUI installer or other means. cd <location where to place ComfyUI>
git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI5.) Download non-official Intel Extension for Pytorch packages here and install the packages with pip. Assuming they are all put in the root of the ComfyUI repository, run this command line. pip install intel_extension_for_pytorch-2.0.110+git0f2597b-cp310-cp310-win_amd64.whl torch-2.0.0a0+gite9ebda2-cp310-cp310-win_amd64.whl torchvision-0.15.2a0+fa99a53-cp310-cp310-win_amd64.whlAgain, I will need to remind you this is unofficial and does have a degree of risk but it should be mostly safe. 6.) Finish the rest of the installation pip install -r requirements.txtAt this point, you should be done with the installation. To run ComfyUI each time from scratch, open a terminal/command prompt. Then run the following command lines replacing <> with your own input: cd <location of ComfyUI>
python main.py <Any extra ComfyUI arguments you want to use> |
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When I try to install this node modifications, it's destroy my ComfyUI build. Because just rolling back all changes was not possible, I completely wiped out Python and Anaconda (as I thought, because despite deleting entries from the registry in AppData\Roaming\Python\Python310\site-packages something strange was still going on), and then follow to next procedure. This is not "ture github way", but at least this can help to someone, who want to launch ComfyUI on Intel Arc for Windows.
Then go to step 9, if no error occured. If you have any problems at this step, such messages like: or See the image:
and go to: To figure out for commented names. If names have "~" at start - remove it. Goto step 8 (copy, enter, and wait to end): 8.
or instead last command, if you have less than 16 Gb memory:
At this point, if all works fine, you can use DDU again, and install latest Intel Arc drivers. Should to work. Also you can optional install WAS node suite, by running "install.bat" in the "ComfyUI\custom_nodes\was-node-suite-comfyui-main" folder. REMEMBER: any additions for ComfyUI can destroy your ComfyUI installation for Intel Arc, because them build for CUDA mostly part, and trying to install it can destroy your Python dependences, critical for ComfyUI working. Don't forget download models! |
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I used IPEX v2.1.10 but it's not working as expected can you tell me whats wrong? |
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Sorry for the late reply but you are using the wrong version of Python and you didn't read my 2nd instruction point properly.
Do not use the newest 3.11 or 3.12 and use version 3.10 with the non-official packages, this will hold until IPEX updates again but it does not work correctly with the latest ComfyUI and IPEX package at the moment. |
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Yes, but I also used cp311 version of ipex, which is for cpython 3.11 right? |
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Yes, which is the core root of the problem. You aren't using the modified packages I have suggested in my instructions and that has not changed from the older v2.0.110+xpu version packages someone else has provided as the newest version of IPEX v2.1.10 does not work with ComfyUI on any OS platform. |
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Reinstall in forced mode, needed dll in place, but still get this error. Can it be relevant to folder rights or upper or lower letter case in "user"? |
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I found out about what is causing it. It's a dependency issue with libuv. I will overhaul the tutorial based on that shortly. For you, you'll need to uninstall the oneAPI GUI installed components and then backtrack and follow steps 3 onwards but then the method I will provide should replace that in a much more easy manner. |
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There really needs to be a better, more updated tutorial for this. Much of the information is stretched out over the thread and mixed up with information between Linux and Windows |
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I'll consider writing one for Ubuntu because it's the only Linux distro on the consumer side supported officially by Intel unless you pay the big money for Red Hat and SUSE support with their enterprise GPUs. |
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Thanks, should to try too. |
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The whole thing about installing the OneAPI AI Analytics toolkit didn't seem necessary though. On a fresh install of Arch, All I did was install Torch 2.0.1 and intel-compute-runtime-bin from Arch repositories, then install the Intel extension for pytorch with the code below
And then from a terminal in the directory where ComfyUI is installed I used
And that line above I added to a start.sh script, which can include launch options for easier usage. But yeah, that was all I had to do and it takes me about 4 seconds to do 20 steps at 512x768. I'm not even sure I needed to get anything from Arch's repository, if so, those packages should be available in any repository, which would make the install fairly simple for any distro. |
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@burntbyhellfire If you don't use Intel Python, you don't need to install the AI Kit. |
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If we both have a GPU of the same specs we could both run some benchmark prompts and settings to see if there really are any performance improvements with doing it that way. I just got a Sparkle A770 16GB. |
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To install on Ubuntu. 1.) Install Linux drivers with the following instructions provided by Intel here sudo apt install python3-pip git3.) Install ComfyUI with the following terminal commands replacing the <> portion with a selection of your choice. cd <Location to put ComfyUI>
git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI4.) Install all the Intel Extension for Pytorch pip Python packages first with this terminal command. python -m pip install torch==2.0.1a0 torchvision==0.15.2a0 intel-extension-for-pytorch==2.0.110+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/5.) Finish the rest of the dependency installation with this terminal command: pip install -r requirements.txtInstallation should be done at this point. To run ComfyUI, one can type in the following terminal commands replacing <> with your own input: cd <location of ComfyUI>
python main.py <Any extra ComfyUI arguments you want to use>For other Linux distros outside of Arch Linux or Ubuntu, one will need to manually install the Intel compute runtime, git, a Python with a version supported by Intel Extension for Pytorch like 3.10 as of the time of this writing or using Intel's Python from the AI Kit which will provide that, pip, and any other dependencies required according to your own Linux distribution's package manager or install scripts but one should be able to then just follow step 3 and onwards without any issue afterwards. |
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I've updated the Arch Linux setup guide for the latest IPEX and ComfyUI, without oneAPI AI Kit. If anyone wants to uninstall the previously installed AI Kit, it's available: cd /opt/intel/oneapi/installer
sudo ./installer --action remove --product-id intel.oneapi.lin.aikit.product --product-ver 2023.1.0-31760
# if you don't need
paru -Rsc libxcrypt-compat |
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New Patch!Thanks to vladmandic/automatic for the code. contributors Basically, you just need to copy Then modify try:
import intel_extension_for_pytorch as ipex
if torch.xpu.is_available():
xpu_available = True
+ from attention import attention_init
+ ok, e = attention_init()
except:
passIt could partially fix intel/intel-extension-for-pytorch#325. (so f**k you, intel) |
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That's more of a workaround, I've seen his code but I didn't think @comfyanonymous would enjoy special casing his code with a specific attention implementation that would work for Intel GPUs only for working around the issue which is why I didn't submit a variant it when I wrote the patches for enhanced IPEX support. Doing manual memory management like this is a pain in Python and doesn't look particularly nice. I think Intel has to fix it on their end, asking end users of IPEX to do this to every project that implements IPEX is untenable. |
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I couldn't find any performance gains with Ipex in tests I ran in ComfyUI before, and after setting up an environment and running Comfy from it. |
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interesting tho, that i didn't do anything with modules/intel/ipex/attention.py, but problem with 4GB limit is gone after patching p.s. error still continue to occur ^_^ |
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It seems that only older versions of |
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Cool... Got it working with WSL2 using Arch. Followed the instructions at the top, as well as installed jemalloc paru(root/native environment), openmp via pip(venv). There are issues with the env vars as Arch is pulling my windows env vars through. So I some times have to re run the setvars.sh. I get warnings about libpng when I run via python or ipexrun. Everything still works though. I generally run through ipexrun but add xpu to the command i.e.
Apart from some memory overruns I've had no issues the last few days. |
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anybody can tell where intel store their patches for pytorch? |
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You can find these "patches" here but it's really not that much different over just compiling the source tree provided. |
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thanks! |
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Yes, and pytorchvision and other associated packages. |
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Hi to all, i'm also here to trying to understand if ipex is good enough for my arc a770, 'cause for what i evaluated so far, and as simonlui suggest, the dev nightly 2.8xxx version of torch works better than ipex 2.6+xpu. I tested in an ipex2.6+xpu venv, with sdxl-1,0-base, both in comfyui and in jupyter stablediffusionXLpipeline, with 34 seconds average for a 768 img with 30 steps, So i'm asking if i need to declaree some flags when starting comfy or when importing the models in the pipeline for activating the real performance that ipex should offer? i'm missing something? or we have to stay with nightly xpu pytorch versions? It will be also great if comfyui could implement openvino, as it seems for my experience with my arc a770 the better option in terms of performance. |
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Hey, I saw that you successfully set up and used ComfyUI on your system. I’m trying to set it up on my Windows 10 Pro machine with 64 GB RAM and an Arc A750 GPU, but I’m running into some issues. I trying to set it up up for 2 days now. If all things go right the generation doesn't work. |
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i'm on linux, so i followed the installation instructions on https://github.com/comfyanonymous/ComfyUI, you have to setup an python venv or conda environment, with ipex or better without it, use the nightly 2.8xxx+xpu version,then clone the comfyui github and run the requirements.txt in the venv but put a # to disable the packages already in your venv, and install the remaining with --no-deps, check if torch sees your 'xpu' in python : |
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File "C:\ComfyUI2\ComfyUI_windows_portable\python_embeded\Lib\site-packages\torch\cuda_init_.py", line 971, in current_device C:\ComfyUI2\ComfyUI_windows_portable>pause |
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Does anybody have a list of stable diffusion models compatible with a B580? |
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Generally anything ComfyUI supports models-wise is what any piece of hardware supported by ComfyUI should be able to run as well. If not, that is a bug. So yes, it should be everything. |
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thanks! |
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very new to this and I probably don't understand everything going on .. but, are the ipex builds only going to work on with Intel cpus and Intel Arc cards? i have a amd cpu (5600G) with Intel arc b580 ... no matter what docker version of comfyui I've tried, including just the intel base image to test pytorch, I get some type of error like this. ollama docker works fine passing thru the same device (/dev/dri). i can also run comfyui with pytorch on the ubuntu vm host fine. unfortunately, I don't have a intel cpu to test with the card ... comfyui-ipex | [notice] A new release of pip is available: 25.0.1 -> 25.1.1 |
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Are you using the Docker from https://github.com/YanWenKun/ComfyUI-Docker/tree/main/xpu or no? I would generally want to try that over doing something like running my outdated Docker or any other Docker image. The fact other Docker stuff works and can use your GPU properly but not with whatever you did generally indicates the image was built wrong or etc. |
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@simonlui I notice in this link https://github.com/YanWenKun/ComfyUI-Docker/tree/main/xpu that Flux and SD3.5 failed. You think that is because the card only has 12GB, and those failed models should work if we stack 2 or 3 of these cards to give us 24GB, 36GB etc? |
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It's more or less a test out of the box, I would imagine. Based on my experience with the unmaintained Docker image I published and used, anything can work inside Docker as with bare metal. It's just that running the heavier models rely more on needing to use stuff that is more custom and research paper based trading off quality of some kind for VRAM savings or speed and etc. Mostly with those models, you will want to use something like quantization to run them on something like a B580 which would provide you with the biggest savings. But just besides that, yes, Intel still has less optimizations and etc. for VRAM compared to something mature like Nvidia or even AMD at this point, so you will need to make the best of the situation. |
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I wanted to know why ipex? Since just torch works a thousand times better than with ipex installed. |
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Because I'm an idiot with comfyui and everything related (like docker). Let me try and build a new docker tonight with just pytorch and see if it works. I've been thru too many failed iterations base os and/or docker |
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IPEX nowdays adds on optimizations that Intel hasn't merged into Pytorch proper so it is effectively a way to run inference faster with new stuff Intel has but didn't fit the release cycle. In the beforetimes when Intel hadn't upstreamed to Pytorch and made official builds like when this discussion thread was started, it was the only way to run ComfyUI via installing Intel's entire Pytorch branch. Nowadays, just Pytorch itself has worked since Pytorch 2.7 for XPU as a general rule. Any Pytorch version older like the fastest version at the time of writing this available with Pytorch 2.3.1, you need IPEX. |
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Running WAN2.1 I2V 480P with CausVid lora on A770/B580With CausVid lora, you can generate video with only 6~9 steps. Requirements
Note that, You should use fp16 or bf16 model without casting dtype, because using fp8 model or casting to fp8 cause black image. Prerequisites
How to
Generation speedSetttings: 512x768, 93 length(frame), 9steps
ResultComfyUI_00258_.webm |
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@simonlui I was tested that long ago, so don't remember the state I failed to partial load. |
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I use this setting with B580, spent 37 minutes to generate the same animation on bf16 model at 234.26s/it. After a few trial and error figured out lower length could help, now generating at 45s/it. |
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@simonlui on torch2.5.1+xpu and B580, partial loading cause "The model is mixed with different device type" without |
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I dunno what the issue is, because I used the same offloading workload as you. But yeah, if it doesn't work with that error, then you should disable |
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@bedovyy Was it converted to something else during inference? I've tried to set manual casting to "torch.fp8_e4m3fn" in model loading and got "oneDNN does not support fp8_e4m3fn" error. B580. |
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Quick warning for others to not make my mistake: When you have https://github.com/neuratech-ai/ComfyUI-MultiGPU installed everything runs on CPU. |
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ComfyUI_ExtraModels has |
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Hi I filtered out these log messages from my comfyUI installation: |
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That is normal logging unfortunately from Intel's optimization pass that is on by default. Small price to pay for the fact it runs faster than normal Pytorch for now. |
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@bedovyy what was your workflow for Flux1 Dev? I have been experimenting and am having no success yet. |
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That's interesting! Did you just swap the load diffusion/dual clip nodes for the gguf versions? |
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a GGUF with flux1-dev-Q4_0.gguf for the model and Dual CLIPLoader with the same clip_.safetensors and t5xxl_f8_e4m3fn.safetensors. Also i put couple of unload model a before sampler an VAE |
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@bedovyy @spaceaje, can you share your teacache (and maybe triton) version? I get AttributeError: module 'triton' has no attribute 'autotune'. |
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@tzekeong I think teacache doesn't use triton. torch compile may use triton, but I failed to using it on B580. |
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let me try the workflow w/o torch compile, but I already resolve the issue by compiling triton. refer to https://github.com/intel/intel-xpu-backend-for-triton/blob/main/.github/WINDOWS.md. |
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Does anyone know if it's possible to run Chroma on an Intel GPU? I can't get it to work properly on my A770/16GB, I'm getting "The model is mixed with different device type" error. |
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Which version of torch do you use? |
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Yeah, im running chroma on my intel b580 steel legend. python 3.10.6 pytorch version: 2.5.1+cxx11.abi |
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Is UR_RESULT_ERROR_OUT_OF_DEVICE_MEMORY error on B580 GPU OK ? I tried different settings, but crashes still happening sometimes. |
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For SDXL, no. Any custom nodes in use? Some of them can cause this. |
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Thanks, this narrows the problem. |
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I also facing UR_RESULT_ERROR_OUT_OF_RESOURCES error |
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I've tried to bypass ReActor node, but error keeps ( |
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According to adjacent reports about this I've seen, it is truly you running out of memory. Unfortunately at this time, it's not quite clear what would cause Intel to to know what can be causing it. Usually to debug, you will want to start out with a stock SDXL generation pipeline like the one in Comfy's default pipeline and then slowly add things back in to see what the cause is but for 99% of users, that is over their heads to figure out given the amount of stuff going on and things to tweak. |
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This error looks like Intel driver error, because after error screen blinks, and windows play's "device disconnected" sound. All of this problems happening only in ComfyUI so far, in games all runs fine. |
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The driver essentially errored out so you are better restarting the machine when it happened. |
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You can try increasing the |
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Best way to use comfyui on arc for me was. Use pytorch 2.8, and don't
install ipex, on my a580 it generates 1024x1024 images in seconds, It does
not give a vram error, or similar.
Em qui., 10 de jul. de 2025, 09:26, PatsySE ***@***.***>
escreveu:
… Yeah, im running chroma on my intel b580 steel legend.
Look at this image
image.png (view on web)
<https://github.com/user-attachments/assets/90185a62-5ecb-40b2-b7ce-8d8c592e9669>
start command python main.py --disable-xformers --disable-smart-memory
--lowvram --disable-ipex-optimize
python 3.10.6 pytorch version: 2.5.1+cxx11.abi
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Seconds with chroma?? or sdxl? |
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Try Wan2.1 I2V 240x480 length 41 (CFG:1, Step:6) Bug is still here. Use pytorch latest |
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Use Q4_K_M quant, or lower the total frame number. When using Q6_K quant on my A770 16GB, it should be lower than 20. |
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I recently made some improvements to the XPU backend into ComfyUI and mainly added in code so the experimental |
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Did some benchmarking with the new changes with SDXL, my old advice of using Pytorch 2.3 IPEX instead of the latest for the fastest speeds is no longer true at least on my A770 16GB on Fedora Linux running a desktop environment at least for that model. Using the default workflow with SD 1.5 but replaced with SDXL, I get the following on Pytorch 2.3 IPEX for a fresh and warmed up run with 
Here's Pytorch 2.7 IPEX with Here's nightly Pytorch with async offload added with Around a 12-13% increase from 2.3 with around 1.31 it/s to the latest nightly Pytorch with 1.48 it/s here. Will be testing FLUX next. |
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So FLUX basically is SDXL flipped. I suspect there are things in IPEX not out yet in Pytorch proper, as both 2.3 and 2.7 are faster than Pytorch Nightly. 
Pytorch 2.3 IPEX with Pytorch 2.7 IPEX with Nightly Pytorch with So a swing in the opposite direction where 2.3 is 12-13% faster for FLUX than Nightly. Guess we'll see with Pytorch 2.8 releasing first week of August and IPEX following soon how things will perform. |
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ComfyUI now supports Intel Arc Graphics. (#409)
Since the installation tutorial for Intel Arc Graphics is quite long, I'll write it here first.
Intel Extension for PyTorch is currently only available for Linux, so you will need to have a Linux or WSL environment.
Arch Linux (with
paru) are used here as example operating systems.Install Python and PIP:
Install Intel Compute Runtime and Intel oneAPI Base Kit:
Install ComfyUI:
Install Dependencies (via
venv):python -m venv venv source venv/bin/activate pip install torch==2.0.1a0 torchvision==0.15.2a0 intel-extension-for-pytorch==2.0.120+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl-aitools/ pip install -r requirements.txtFor the second start and beyond, venv needs to be reactivated:
source venv/bin/activateSet oneAPI vars:
source /opt/intel/oneapi/setvars.shRunning ComfyUI (via
python):Running ComfyUI (via
ipexrun):Beta Was this translation helpful? Give feedback.
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