4 ms·
Uhh, conda create a new environment first. Conda literally does everything else for you (including the actual hard part , getting your GPUs to play nice with CU
by Der_Einzige 4y ago
Uhh, conda create a new environment first. Conda literally does everything else for you (including the actual hard part , getting your GPUs to play nice with CUDA and to be recognized by pytorch or tensorflow)
Just make a new conda environment, and throw it away if it gets clobbered.
But don't listen to me, I only work for a billion dollar company that does all of its cloud data science using conda, so I must not know what I'm talking about...
- quibono 4y agoI think the point is that conda is great until suddenly it's not because of various compatibility issues. Especially when the errors you get will sound very cryptic to someone who's not used to ML and libraries that use CUDA. That's at least my experience, I've personally always preferred to not use it at all (N=1). Also, you sound very insecure, not sure what the company drop at the end is for.