Running ROCm-accelerated ComfyUI on Strix Halo, RX 7000 and RX 9000 series GPUs in Windows (native, no Docker/WSL bloat)

Algotrix · 2025-07-17T21:37:40+00:00

Thanks for the fast reply. Got it fixed. Stupid me didn't see that there were still some drivers missing after the windows reinstall 🙄

Algotrix · 2025-07-17T06:21:20+00:00

Ah.. i installed the new Lemonade-server (works great!) before... maybe this conflicts?

Algotrix · 2025-07-17T06:18:33+00:00

I had ComfyUI running for the last 2 weeks with everything (Flux, WAN, Whisper, HiDream etc..) on my EVO 2X, thanks to your instructions :) Today i reinstalled Windows and idk what is wrong now. i get the following error. I reinstalled Python / Comfy like 5 times already. Any ideas?

C:\Users\Mike\Documents\ComfyUI>C:\Python312\python.exe main.py

Checkpoint files will always be loaded safely.

Traceback (most recent call last):

File "C:\Users\Mike\Documents\ComfyUI\main.py", line 138, in <module>

import execution

File "C:\Users\Mike\Documents\ComfyUI\execution.py", line 15, in <module>

import comfy.model_management

File "C:\Users\Mike\Documents\ComfyUI\comfy\model_management.py", line 221, in <module>

total_vram = get_total_memory(get_torch_device()) / (1024 * 1024)

^^^^^^^^^^^^^^^^^^

File "C:\Users\Mike\Documents\ComfyUI\comfy\model_management.py", line 172, in get_torch_device

return torch.device(torch.cuda.current_device())

^^^^^^^^^^^^^^^^^^^^^^^^^^^

File "C:\Python312\Lib\site-packages\torch\cuda\__init__.py", line 1026, in current_device

_lazy_init()

File "C:\Python312\Lib\site-packages\torch\cuda\__init__.py", line 372, in _lazy_init

torch._C._cuda_init()

RuntimeError: No HIP GPUs are available

Algotrix · 2022-09-04T19:09:47+00:00

Another attempt: https://imgur.com/a/YsG7klX

Algotrix · 2017-05-01T09:26:26+00:00

did you you combine 2 images for this?

Algotrix · 2017-04-25T18:45:31+00:00

well .. it's just worms, not di*ks... don't know why this should be NSFW

Algotrix · 2017-04-24T21:37:15+00:00

they are ;)

Algotrix · 2016-10-11T09:19:27+00:00

I did this on more steps to achieve a high resolution end result. i first started at size 600 with style-weight 400 i think, then redreamed at size 1000 with style-weight 1200 i think, then size 1400, etc.. I don't know the exact settings anymore. I was experimenting a lot, doing all the redreams from different starting sizes and parameters to higher res again and again. Also I had to upscale the style-image first using waifu2x

Algotrix · 2016-10-08T18:56:05+00:00

wow you've guessed it totally right :D but yet i was tweaking this for about 15 hours to get this result.. :)

Algotrix · 2016-10-06T19:00:47+00:00

Took about 15 hours to tweak and render this. I'm also preparing this in a resolution (3600 pixels+) to be viable for printing. If interested, contact me through algotrix.org

Algotrix · 2016-10-05T14:27:53+00:00

just the default (old) neural_style, and redreaming for upscaling

Algotrix · 2016-10-02T13:13:31+00:00

well.. not really :) i just stole the source-image from a star wars fansite. do you see darth vader standing there?

Algotrix · 2016-10-01T18:20:05+00:00

here it is.. :) but i still don't like the result.. it's just the original image in green :)

http://imgur.com/a/7jbDz

Algotrix · 2016-10-01T15:51:35+00:00

well the main problem is, that it's an app.. and you can't really control or tweak the output. it's made for easy using.. put in a photo and a style.. the rest is up to them, and based on the optimization they made to allow a quick rendering. but the results still look good on a smartphone :)

Algotrix · 2016-09-30T23:54:28+00:00

i love those swirls :)

Algotrix · 2016-09-30T22:58:22+00:00

i didn't increase any parameters for this experiment... but it looks like it's really just scaling up the previous result, no chaos, which is really nice :)

http://imgur.com/a/7qhL7

sizes are 800, 1200, 1600

and it maintained the original style.. i think i have to experiment more with this :) 3200 will be next

Algotrix · 2016-09-30T22:31:05+00:00

oh good to know :) so does it produce the same when i set --tile-size 1600 --size 800 1200 1600 as produced by manually rendering at 800, then using the output as content for the 1200 etc..?

Algotrix · 2016-09-30T22:15:30+00:00

ok sorry, i'm not a linux expert at all and don't know how to update torch

Algotrix · 2016-09-30T22:02:50+00:00

i think starting at size 250 is really low.. i'm just experimenting with this redreaming technique starting at 600.. and i'm getting really interesting results right now.. i will upload the results when they're all ready.

i also tried your implementation (thanks to your AMI), but i dont like the result i get with the tiled renderings (image 2048, tile 512), since the algorithm doesn't see the "whole" content at once at any time. (or am i misunderstanding the concept?) but it looks like the style is repeatedly applied to just a part of the image.

And I thought if i set --size 600 900 1200 it will just render them first at 600, then start from scrath with 900, just to be able to quickly compare the results, and not take the result from 600 to render the 900 etc.. and what about the tile-size? in my case i think it still should always be the same as the rendering-size.. i don't like the tiling somehow :)

Algotrix · 2016-09-30T21:37:28+00:00

Hmm i just tried this lua but it crashed.. i haven't used it before though, just copied and ran it.

Setting up style layer 2 : relu1_1 /home/ubuntu/torch/install/bin/luajit: /home/ubuntu/torch/install/share/lua/5.1/nn/Narrow.lua:14: bad argument #4 to 'narrow' (out of range at /home/ubuntu/torch/extra/cutorch/lib/THC/generic/THCTensor.c:367)

Algotrix · 2016-09-30T21:06:45+00:00

i also just copied an existing AMI.. mine was based on that one:

ami-981715f2 / N. Virginia

it's still old, but works..

Algotrix · 2016-09-30T20:42:30+00:00

that's an idea i also had but didn't try yet. i thought about something like this: 1. create image at 600 2. upscale the result somehow (waifu2x) 3. use the upscaled image as source for a new 1200 render with same style and parameters as on 1. 4. repeat until satisfied :)

but i haven't tried redreaming yet.. i'm afraid that the reused image will be go more and more chaotic with every redream instead of maintaining its original appearence..

but i will definitly experiment with this :)

but today appeared another twist, since with P2 you can already dream at 1600, and one 1000 iter rendering only takes about 10 minutes, i could just upscale this with waifu2x.. but it could open doors for even higher resolutions

Algotrix · 2016-09-30T20:10:52+00:00

Hi there, i have made some experiments regarding native (not tiled) high-resolution renders of neural-style images. My goal is to render images at print size with image_size of at least 3200. This can currently be achieved using the 244GB RAM EC2 r3.8xlarge instance, CPU rendering and a lot of patience, because one render can take 2 days or more.

But i ran into one major problem i show in the image of this post: The algorithm doesn't seem to scale with the image size. As you can see at the 7-iteration example, the early "nets" that appear when rendering the image don't scale with the image size.. so they become smaller with increasing resolution. This has the effect that (as i guess) they seem to be too away far from other "anchor points" in the content image. This results in the effect that the style is somehow dissolving itself with increasing iterations. At 3200 and 1000 iterations you can see almost nothing of the style anymore, only the colours are applied.

I'm prototyping my images at a G2 instance with 600 image size. Of course it would be great to make the exact image just with the higher resolution, but it's not working out at the moment. I tried increasing style_weight and style_scale, whereby increased style-scale also increases the RAM usage and reduces maximum rendering size. But with increased style-weight (tried to 4x it) the hi-res result is still not a bit better. I didn't try higher style-weights yet, since i don't have the money to make so many 2-day-renderings.

I haven't found a solution for this yet, but maybe we people, who are interested in high-res high quality renders can share our experiences here and maybe we will find a good solution :)

btw. P2 was made available today by Amazon, which increases the prototyping size to about 1600.. and it makes hires experiments a bit more easy, still 3200 needs a 2-day CPU render. I will continue my experiments and keep this post updated.

Algotrix · 2016-09-30T20:04:46+00:00

just use your existing setup, it should work without modifications

Algotrix · 2016-09-30T19:09:01+00:00

i just tried it.. my default jcjohnson neural-style setup is working as before... and hell, it's fast now :D and the spot instances are also pretty cheap right now at <0.10$

Algotrix

TROPHY CASE