@ptrblck , greetings.
It seems that I’m facing this issue using nvidia-docker2, though that maybe you can assist to figure it out.
Particularly, may it be that the nvidia-docker2 creates such recompiling because of its design ?
Can you take a look stackoverflow issue.
It’s not a pure pytorch issue, but maybe an nvidia-docker one, but maybe from a fast look at nvidia-docker design you could make some efficient conclusion for this issue in my setup and environment.
Particularly, do you think I should try install CUDA8.0 drivers on my host and try to see if I can make the connection between those drivers and the docker container (not sure if it is possible to manage in such way drivers, but that’s another question for CUDA I guess)?
Oh, forgot my Ubuntu 20 doesn’t support CUDA8.0.
Well, anyway it could be useful if you could take a look and tell me on which end in that case does seem to be the problem.