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Looking a bit more into it, it seems like torch comes with even more bloated dependencies. It end's up installing a bunch of cuda stuff, and I don't fully understand why.

Looking a bit more into it, it seems like torch comes with even more bloated dependencies. It end's up installing a bunch of cuda stuff, and I don't fully understand why.

oh yeah, on linux pip install torch gets you full cuda support, you need to specify pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cpu to get the cpu-only build. Check out the installation matrix here: https://pytorch.org/get-started/locally/ . I don't know whether you can specify index url in requirements txts though.

Seems like we can specify it in the requirements.txt, but you can't specify it for a single package: pypa/pip#12233

Will this cause problems with other packages? I'd hope that the url is "pure".

I'll mark this as a draft while we decide what to do. In the meeting we discussed potentially switching to conda environments or to pixi.

I'll mark this as a draft while we decide what to do. In the meeting we discussed potentially switching to conda environments or to pixi.

it may not be bad to have this or a patch at the integration tests repo (whatever y'all prefer) in the meantime just for the sake of having the integration tests ci pass.

Yeah, that's a good point. How for now we just switch to testing ML on macOS (which doesn't have the extra nvidia bloat) and revert to the original requirements?

Yeah, that's a good point. How for now we just switch to testing ML on macOS (which doesn't have the extra nvidia bloat) and revert to the original requirements?

That does sound good to me. Actually, even jax may bring in bloat on linux but I don't remember off the top of my head.

I think this needs a title change now to reflect what it actually does but should be good otherwise

We're fully green over at integration tests again :)