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WSL problems but not related to CUDA:

- need a patch to expose ports for services in WSL to network (WSLHostPatcher)

- the Virtual Hard Disk (vhdx) does not free unused space easily and it can grow quickly. I ended up just symlinking my code and dataset folders to mounts, not saving a lot of data inside the vhdx

- beware of upgrades etc. I think I nuked my WSL 2x due to config issues. Having all your code/data on mounts also makes this easy.

related to ML/CUDA:

- how you install pytorch + CUDA matters. I ended up just installing from `conda --channel fastchan` and don't touch it. not ideal but it works

- Don't forget to configure the RAM allocation in case you need a lot

- I haven't tried running a CUDA Docker on WSL. May be an easier way to do this.

Running on Windows directly is also an option. I choose to run on WSL because most learning resources/documentation refer more to Linux installs and setups.




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