CUDA driver fails to initialize in WSL

### Is there an existing issue for this?

- [x] I have searched the existing issues

### Current Behavior

When running profiler in WSL for CUDA-enabled Pytorch code, CUDA driver fails to initialize. Specifically, this happens after entering the `memray.Tracker` context manager.

```sh
$ python -m memray run -q -c 'import torch; print(torch.cuda.is_available())'
False
```

### Expected Behavior

CUDA driver being able to initialize,

```
$ python -m memray run -q -c 'import torch; print(torch.cuda.is_available())'
False
```

### Steps To Reproduce

1. WSL2 (Ubuntu 24.04), CUDA 12.7
2. Prepare python env:
```sh
$ pip install memray
$ pip install torch --index-url https://download.pytorch.org/whl/cu126
```
3. Run `python -m memray run -q -c 'import torch; print(torch.cuda.is_available())'`

### Memray Version

1.16.0

### Python Version

3.12

### Operating System

Linux

### Anything else?

I checked that this happens exactly in WSL environment. If I try to reproduce this in a Docker container of ubuntu:22.04 image, Docker engine being installed in the same WSL environment, CUDA successfully initializes.
Having read about [supported environments](https://bloomberg.github.io/memray/supported_environments.html#supported-operating-systems), I'm still not quite sure if WSL is supported or not.

Start by reproducing `python -m memray run -q -c 'import torch; print(torch.cuda.is_available())'` in WSL2 Ubuntu 24.04, then compare it with the reported Docker result and the behavior inside `memray.Tracker`. Done means the CUDA driver initializes successfully when profiling the PyTorch command, with the expected CUDA availability result documented.

Written by the indexing model from the issue text.