Closed anderslanglands closed 2 years ago
device=cpu
works but is obviously quite slow
Cudnn can be disabled while still using CUDA by adding
torch.backends.cudnn.enabled = False
to the code.
Thanks for your reply! Where would I put that... just somewhere at the top of main.py? EDIT: sticking it just after the torch import seems to have worked. Thanks!
And if I do want to use cuDNN what do I do in that case? Just install CUDA toolkit and have it in my LD_LIBRARY_PATH?
The cudatoolkit installed by conda should be all you need, even for cudnn. Perhaps a different CUDA version might help. But already disabling cudnn should take you a long way (I remember having had similar problems sometimes).
Thanks for your help!
I'm getting the following error when trying to run:
I installed as per instructions in the README. I'm on a pretty fresh Ubuntu 20.04, with NVIDIA driver 470 and an A6000. I don't have a CUDA toolkit installed aside from the one installed by conda.
I've also tried this on Ubuntu 18.04 under WSL2g and native Ubuntu 22.04. In some cases I get the traceback, in others it just sits there for a very long time (it may be that the trace would have printed eventually I just got tired of waiting).
Any pointers you can give me would be appreciated.