Part of https://github.com/astral-sh/uv/issues/4392
We shouldn't link to PyPI, and dropping the workspace-level
documentation link should mean that we get the auto-generated `docs.rs`
links.
This PR enables `--torch-backend=auto` to automatically detect Intel
GPUs. It follows up on
[#14386](https://github.com/astral-sh/uv/pull/14386).
On Windows, detection is implemented by querying the
`Win32_VideoController` class via the [WMI
crate](https://github.com/ohadravid/wmi-rs/tree/v0.16.0).
Currently, Intel GPUs (XPU) do not depend on specific driver or toolkit
versions to determine which PyTorch wheel to use.
Following a CI failure in https://github.com/astral-sh/uv/pull/15028,
ensure that all workspace crates are inheriting the MSRV and other
workspace configuration from the workspace root.
## Summary
If you use `--torch-backend=auto`, we want to avoid selecting (e.g.) a
`+cu124` build of `torch` alongside a `+cu126` build of `torchvision`.
## Summary
This is a prototype that I'm considering shipping under `--preview`,
based on [`light-the-torch`](https://github.com/pmeier/light-the-torch).
`light-the-torch` patches pip to pull PyTorch packages from the PyTorch
indexes automatically. And, in particular, `light-the-torch` will query
the installed CUDA drivers to determine which indexes are compatible
with your system.
This PR implements equivalent behavior under `--torch-backend auto`,
though you can also set `--torch-backend cpu`, etc. for convenience.
When enabled, the registry client will fetch from the appropriate
PyTorch index when it sees a package from the PyTorch ecosystem (and
ignore any other configured indexes, _unless_ the package is explicitly
pinned to a different index).
Right now, this is only implemented in the `uv pip` CLI, since it
doesn't quite fit into the lockfile APIs given that it relies on feature
detection on the currently-running machine.
## Test Plan
On macOS, you can test this with (e.g.):
```shell
UV_TORCH_BACKEND=auto UV_CUDA_DRIVER_VERSION=450.80.2 cargo run \
pip install torch --python-platform linux --python-version 3.12
```
On a GPU-enabled EC2 machine:
```shell
ubuntu@ip-172-31-47-149:~/uv$ UV_TORCH_BACKEND=auto cargo run pip install torch -v
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.31s
Running `target/debug/uv pip install torch -v`
DEBUG uv 0.6.6 (e95ca063b 2025-03-14)
DEBUG Searching for default Python interpreter in virtual environments
DEBUG Found `cpython-3.13.0-linux-x86_64-gnu` at `/home/ubuntu/uv/.venv/bin/python3` (virtual environment)
DEBUG Using Python 3.13.0 environment at: .venv
DEBUG Acquired lock for `.venv`
DEBUG At least one requirement is not satisfied: torch
warning: The `--torch-backend` setting is experimental and may change without warning. Pass `--preview` to disable this warning.
DEBUG Detected CUDA driver version from `/sys/module/nvidia/version`: 550.144.3
...
```
Zanie Blue
Zsolt Dollenstein
Yu, Guangye
konsti
Charlie Marsh