I’m working on a Google cloud instance where I’m hoping to run a Docker container, so I’ve tried several ways of doing that.
I’ve figured out that if I don’t use Docker at all and install PyTorch (and condatoolkit==10.1) with conda, it suddenly works, but even if I used the same method of installation of PyTorch (with conda) inside Docker, it again returns torch.cuda.is_available() to be False. As for the image I’m building my Docker image from, I’ve tried several ones (like a PyTorch image and some other images that claim to have cuda 10.1 installed).
The only new info that I have is that it works outside Docker, but not inside (a problem I’ve never had at my work servers)…
I can try installing it again inside Docker to reproduce the logs, but I’m not sure installation is the problem, but rather some Docker<->Nvidia problems… although I’ve never had those before.