Comment on: Running on WSL2 Ubuntu 22.04 fails

### SUMMARY I've tried with --backend=cpu, it works fine, and also seems to work when --backend=gpu is specified. Benchmarking fails on GPU backend but works fine in CPU. So I'm confused. Note that I did this with model locally downloaded in /model directory (to save on bandwidth as I was testing), and while downloading from huggingface. All this was done in WSL2, Ubuntu 22.04.5 LTS. **GPU IS ACCESSIBLE FROM TORCH** As an experiment, I installed pytorch in another virtual environment and tested if it can access the GPU, and I got these results: ``` (.venv) nemisis@nemisis-BLACK:/mnt/e/sandbox/parlor/test-cuda$ python torch_cuda_test.py Is CUDA available? True CUDA device count: 1 CUDA current device: 0 Torch CUDA device: CUDA device name: NVIDIA GeForce RTX 4080 GPU ``` **DOCKER** I also tried seeing if parlor works in docker as it is more widely available than WSL (image built FROM nvidia/cuda:12.8.0-devel-ubuntu24.04) with more or les...