CUDA won't detect GPU in WSL

Nobody has claimed this yet.

I tried setting up Pytorch with CUDA in WSL but it just doesn't pick up my GPU. `torch.cuda.is_available()` returns `False`.
----------------------------------------------------------------------------------------------------------------------------
```
#include
#include

int main(int argc, char** argv) {
int driver_version = 0, runtime_version = 0;

cudaDriverGetVersion(&driver_version);
cudaRuntimeGetVersion(&runtime_version);

printf("Driver Version: %d\n"
"Runtime Version: %d\n",
driver_version, runtime_version);

return 0;
}
```
This code, compiled with `nvcc`, just returns
```
Driver Version: 0
Runtime Version: 0
```
-------------------------------------------------------------------------------------------------------------------------
I'm on `Microsoft Windows [Version 10.0.19044.2251]`

And this is what `torch.utils.collect_env` outputs:
```
PyTorch version: 1.10.0+cu111
Is debug build: False
CUDA used to build PyTorch: 11.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.4 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31

Python version: 3.9.15 (main, Nov 24 2022, 14:31:59) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.31
Is CUDA available: False
CUDA runtime version: 11.1.105
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] torch==1.10.0+cu111
[pip3] torchaudio==0.10.0+rocm4.1
[pip3] torchvision==0.11.0+cu111
[conda] numpy 1.23.5 pypi_0 pypi
[conda] torch 1.10.0+cu111 pypi_0 pypi
[conda] torchaudio 0.10.0+rocm4.1 pypi_0 pypi
[conda] torchvision 0.11.0+cu111 pypi_0 pypi
```
This is `nvidia-smi` ran on the Windows host.
```
Sat Dec 03 00:22:29 2022
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 457.51 Driver Version: 457.51 CUDA Version: 11.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce GTX 1060 WDDM | 00000000:01:00.0 On | N/A |
| N/A 65C P5 8W / N/A | 750MiB / 6144MiB | 28% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
```
-----------------------------------------------------------------------------------------------------------------------
I've tried what [this person suggested doing](https://github.com/pytorch/pytorch/issues/73487#issuecomment-1115441977), which is to install everything through `conda` in a new environment in a new WSL2, but it didn't work.

[From this thread](https://github.com/microsoft/WSL/issues/8174), there supposedly should be an `nvidia-smi` binary in `/usl/lib/wsl/lib/` but, on every single one of my WSL2 instance, there's only `. .. libd3d12.so libd3d12core.so libdxcore.so` there.

Does anyone have any ideas how I might get this working?
Thanks

Start with the WSL2 GPU integration context and the reported /usl/lib/wsl/lib path, then compare the behavior described in the linked WSL and PyTorch issue threads. Reproduce the CUDA probe and torch.utils.collect_env output; done means identifying why GPU detection fails and documenting or validating a concrete fix.

Written by the indexing model from the issue text.