It is an extension of the capability of WSL, giving you that sweet convenience of the DirectX API with your existing ML project. Of course, this extension makes your project incompatible with desktop Linux once adopted.
Not necessarily. It is not possible to access the GPU in WSL at all right now, so I need to dual boot which also means dealing with Linux desktop compatibility issues with my laptop.
As long as I can use the same ML framework (without DirectX API), then this poses no compatibility issues at all. It just means I can develop & run my ML code in WSL.
It's way more of a pain, due to a lot of legacy constraints in windows. It's easy to overflow pathnames and command lines that then get silently truncated. Doing ML dev work is for sure easier on a Linux env than a pure Windows env. it's not impossible on Windows, but def much nicer in Linux.
Except your ML project is accessing the DirectX API through another cross-platform API layer (CUDA). And the purpose of running WSL is that you ultimately hope to deploy to Linux servers (which Microsoft hopes will be on Azure).
It is an extension of the capability of WSL, giving you that sweet convenience of the DirectX API with your existing ML project. Of course, this extension makes your project incompatible with desktop Linux once adopted.