Issue Installing Apex in WSL Environment

🐛 Bug

I'm having a problem installing Apex in a WSL environment. It seems the installation script for Apex is trying to find the CUDA installation directory and run the nvcc -V command. In a WSL environment, despite CUDA being supported through the NVIDIA WSL driver, there may not exist a proper CUDA installation directory, and nvcc may not be added to the PATH environment variable.

To Reproduce
I attempted to install Apex in WSL using the following commands:

git clone https://github.com/NVIDIA/apex
cd apex
pip install -v --disable-pip-version-check --no-cache-dir ./

I then received the following error:

File "/home/ldd/nlp/apex/setup.py", line 130, in <module>
  _, bare_metal_version = get_cuda_bare_metal_version(CUDA_HOME)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/ldd/nlp/apex/setup.py", line 17, in get_cuda_bare_metal_version
  raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True)
                                        ~~~~~~~~~^~~~~~~~~~~~~
TypeError: unsupported operand type(s) for +: 'NoneType' and 'str'

Expected behavior
I would expect Apex to be installable in a WSL environment without needing a full CUDA installation directory or nvcc.

Environment

OS: Ubuntu 20.04 on WSL 2
Python version: 3.11
PyTorch version: 2.0.1
CUDA version: NVIDIA CUDA 11.3 driver for Windows
GPU models: [e.g. NVIDIA RTX 2080]
Apex version: master branch as of 2023-06-06
GCC version: [e.g. 7.5]
Any other relevant information:
Additional context
I'm trying to run a deep learning project that depends on Apex. I'm unable to run this project as Apex cannot be installed in my WSL environment.

Start with setup.py, especially get_cuda_bare_metal_version and the CUDA_HOME handling shown in the traceback. Reproduce the pip install command in WSL 2, then determine whether installation can work without a CUDA directory or nvcc; done means the documented environment installs Apex without this TypeError.