ROCm VS InvokeAI

ROCm is not spelled out anywhere in their documentation and the best answers in search come from Github and not AMD official documents

"Radeon Open Compute Platform"

https://github.com/ROCm/ROCm/issues/1628

And they wonder why they are losing. Branding absolutely matters.

https://github.com/ROCm/ROCm/issues/1353

Bought in 2020. Stopped working in 2020. Not the latest, but in-production, advertised ROCm-capable, and what I could find during the Great GPU Shortage of 2020.

Maybe so. But it isn't confidence inspiring when I go to see which cards are supported and I see this issue:

https://github.com/ROCm/ROCm/issues/1714

With Nvidia cards, I know that if I buy any Nvidia card made in the last 10 years, CUDA code will run on it. Period. (Yes, different language levels require newer hardware, but Nvidia docs are quite clear about which CUDA versions require which silicon.)

The will-they-won't-they and the rapidly dropped support is hurting the otherwise excellent ROCm and HIP projects. There is a huge API surface to implement and it looks like they're making rapid gains.

Like, there is: https://github.com/ROCm/ROCm.github.io/blob/master/hardware.md but I'm pretty sure that's very very outdated, maybe from 4.x?

Fair enough I'll give you that. Although it is listed as officially supported here, other documentation says it works but is not officially supported.

Do you have a source? The 580 and several older cards are listed as officially supported here, and even some 2xx/3xx cards are listed as unofficially supported.

Some of the GPUs listed in your link are for consumers. For a more extensive list, see https://github.com/ROCm/ROCm.github.io/blob/master/hardware.md

Very conveniently, your linked page (the therein linked pages) do not talk about which GPUs actually do support ROCm. This is probably because AMDs newest cards do not support ROCm in any way, and would guess they don't want the sales pact this lack of feature could cause. Please do evaluate yourself, here: https://github.com/ROCm/ROCm.github.io/blob/master/hardware.md

Probably not, since I have no idea what you're talking about. I've just been using the models that InvokeAI (2.3, I only just now saw there's a 3.0) downloads for me [0]. The SD1.5 one is as good as ever, but the SD2 model introduces artifacts on (many, but not all) faces and copyrighted characters.

[0] https://github.com/invoke-ai/InvokeAI

I actually used the rocm/pytorch image you also linked.

I'm not sure what you're pointing to with your reference to the Fedora-based images. I'm quite happy with my NixOS install and really don't want to switch to anything else. And as long as I have the correct kernel module, my host OS really shouldn't matter to run any of the images.

And I'm sure it can be made to work with many base images, my point was just that the dependency management around pytorch was in a bad state, where it is extremely easy to break.

> Anyways, hopefully this PR fixes the immediate issue: https://github.com/invoke-ai/InvokeAI/pull/5714/files

It does! At least for me. It is my PR after all ;)

The data being flagged is not in that github repo, it's fetched from elsewhere and I don't fancy spending time looking for it. The alert is for 'Sirefef!cfg' which has been reported as a false positive with a bunch of other stable diffusion projects (https://www.reddit.com/r/StableDiffusion/comments/101zjec/trojanwin32sirefefcfg_an_apparently_common_false/, https://www.reddit.com/r/StableDiffusion/comments/xmhukb/trojan_in_waifudiffusion_model_file/, https://github.com/invoke-ai/InvokeAI/issues/2773 )

I haven’t tried it recently, but InvokeAI runs on Mac. Invoke. I used to run on my MacBook, but have since gotten a Win laptop.

There are already a number of local, inference options that are (crucially) open-source, with more robust feature sets.

And if the defense here is "but Auto1111 and Comfy don't have as user-friendly a UI", that's also already covered. https://github.com/invoke-ai/InvokeAI

https://github.com/invoke-ai/InvokeAI should work on your machine. For LLM models, the smaller ones should run using llama.cpp, but I don't think you'll be happy comparing them to ChatGPT.

Stable Diffusion. /r/stablediffusion There are many tutorials on how to set it up locally and use it. InvokeAI is the easiest way to set it up. https://github.com/invoke-ai/InvokeAI

InvokeAI