[mdaniel]

> Cross-Platform

  cpu = [
  "torch @ <https://download.pytorch.org/whl/cpu/torch-2.7.1%2Bcpu-cp312-cp312-manylinux_2_28_x86_64.whl> ; python_version == '3.12'",
  "torch @ <https://download.pytorch.org/whl/cpu/torch-2.7.1%2Bcpu-cp313-cp313-manylinux_2_28_x86_64.whl> ; python_version == '3.13'",
  ]

:-/ It reminds me of Microsoft calling their thing "cross platform" because it works on several copies of Windows

In all seriousness, I get the impression that pytorch is such a monster PITA to manage because it cares so much about the target hardware. It'd be like a blog post saying "I solved the assembly language nightmare"

[gobdovan]

Torch simply has to work this way because it cares about performance on a combination of multiple systems and dozens of GPUs. The complexity leaks into packaging.

If you do not care about performance and would rather have portability, use an alternative like tinygrad that does not optimize for every accelerator under the sun.

This need for hardware-specific optimization is also why the assembly language analogy is a little imprecise. Nobody expects one binary to run on every CPU or GPU with peak efficiency, unless you are talking about something like Redbean which gets surprisingly far (the creator actually worked on the TensorFlow team and addressed similar cross-platform problems).

So maybe the the blogpost you're looking for is https://justine.lol/redbean2/.

[dragonwriter]

> Torch simply has to work this way because it cares about performance on a combination of multiple systems and dozens of GPUs

Or, looked at a different way, Torch has to work this way because Python packaging has too narrow of an understanding of platforms which treats many things that are materially different platforms as the same platform.

[cstrahan]

I think a more charitable interpretation of TFA would be: "I Have Come Up With A Recipe for Solving PyTorch's Cross-Platform Nightmare"

That is: there's nothing stopping the author from building on the approach he shares to also include Windows/FreeBSD/NetBSD/whatever.

It's his project (FileChat), and I would guess he uses Linux. It's natural that he'd solve this problem for the platforms he uses, and for which wheels are readily available.

[esafak]

https://github.com/pypa/manylinux is for building cross-platform wheels.

[mdaniel]

> Python wheels that work on any linux (almost)

So, you're doubling down on OP's misnomer of "cross platform means whatever platforms I use", eh?

[esafak]

I do not know what you are objecting to. I have successfully packaged wheels for MacOS and Ubuntu with manylinux. I presume it works with some others too, but that is what I can personally attest to. Alpine is catered to by the musllinux project.

You should be specific about which distributions you have in mind.