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Comment by stargrazer | Hacker News Reader

Seems to be a Microsoft Windows specific implementation.

Was hoping for something cross platform on to Linux.

As mentioned in the README it's using onnxruntime for inferencing. Onnxruntime is a available on all platforms including Linux. See https://onnxruntime.ai/.

> The current codebase and the resulting Nuget packages target Windows and use DirectML, however only small sections of the code utilize Windows specific APIs, and thus could be ported to other platforms with minimal effort.

Okay... what's stopping them from doing so? The effort?

If it were trivial, that statement wouldn't exist.

Well, that's a little uncharitable, isn't it? Assuming the developers primarily use Windows, they probably just don't have much priority for it; there's probably a lot of things they could do with the time. Perhaps they don't even have a setup to test it, and even as a staunch Linux user, I can't blame someone for not wanting to mess with all of the GPGPU drivers and non-sense.

Just trying to be fair here.

> I can't blame someone for not wanting to mess with all of the GPGPU drivers and non-sense.

Thanks for the downvote and for proving my point for me. That was literally exactly what I said. :)

But yeah, if you say something is "simple" and you can't do it yourself, then it's most likely not.

The misunderstanding here is that I am referring to getting Linux GPGPU to work in the first place, not porting the code itself. Presumably they are suggesting that one of us Linux weirdos who already have gotten ROCm and/or CUDA working could do it with relative ease. That said, I have not attempted to verify the veracity of that assertion, but I think it's what they meant.

Though even if they could just do it, and have everything they need to do it, that doesn't mean they're lying. It really could just not be a priority.

So it's back to the effort right? It's not easy afterall!

Well, with that line of thinking, definitely. Because of course, FIRST, you have to invent the universe.

There is sometimes a wide gulf between simple to implement and easy to verify. They may not have a Linux box set up with the hardware, drivers and development environment to build ML code. In that case even if the fix is simple, testing it and verifying it works is less simple. But anyone interested in using it on Linux would need to do that setup as a prerequisite anyway.

Plenty of open source projects only release on one OS because that's the one the developer uses, even if porting them would not be difficult.

Ah, so completely unusable. Got it.

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