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Uv and Ray: Pain-Free Python Dependencies in Clusters

anyscale.com

44 points by robertnishihara 6 months ago · 10 comments

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lz400 6 months ago

Unfortunately uv is usually insufficient for certain ML deployments in Python. It's a real pain to install pytorch/CUDA with all the necessary drivers and C++ dependencies so people tend to fall back to conda.

Any modern tips / life hacks for this situation?

  • rsfern 6 months ago

    Are there particular libraries that make your setup difficult? I just manually set the index and source following the docs (didn’t know about the auto backend feature) and pin a specific version if I really have to with `uv add “torch==2.4”`. This works pretty well for me for projects that use dgl, which heavily uses C++ extensions and can be pretty finicky about working with particular versions

    This is in a conventional HPC environment, and I’ve found it way better than conda since the dependency solves are so much faster and I no longer experience PyTorch silently getting downgraded to cpu version of I install a new library. Maybe I’ve been using conda poorly though?

  • Kydlaw 6 months ago

    You should give a try to https://pixi.sh/latest/ (I am not involve in the project).

    They are a little more focus on scientific computing than uv, which is more general. They might be a better option in your case.

  • devjab 6 months ago
    • lz400 6 months ago

      the problem is that you still need to install all the low level stuff manually, conda does it automatically

      • gcarvalho 6 months ago

        I was pleasantly surprised to try the guide out and see that it just worked:

            λ uv venv && uv pip install torch --torch-backend=auto
            λ uv run python -c 'import torch; print(torch.cuda.is_available())'
            True
        
        This is on Debian stable, and I don't remember doing any special setup other than installing the proprietary nvidia driver.
      • pcwelder 6 months ago

        This script has been sufficient for me to configure gpu drivers on fresh ubuntu machines. It's just uv add torch after this.

        https://cloud.google.com/compute/docs/gpus/install-drivers-g... (NOTE: not gcloud specific)

  • miohtama 6 months ago

    Would it be possible to use Docker to manage native dependencies?

jessekv 6 months ago

It would be a fun callback if the demo was a factorial server:

https://joearms.github.io/#2013-11-21%20My%20favorite%20Erla...

chatmasta 6 months ago

A whole blog post and nine comments and nobody has made the pun about UV Rays?!

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