I am looking for a guide to install Pytorch successfully , I have a system where I use cuda toolkit == 11.2.2 for tensorflow , but now I want to install pytorch for same version of cuda which is 11.2.2 ,
I just want to keep my installations minimum and don’t wan’t to install different cuda versions for pytorch and tensorflow.
so please help me installing pytorch capable to run on gpu without reinstalling any new cuda libraries
You could build PyTorch from source as described here using your locally installed CUDA 11.2 toolkit.
Thanks for the reply. But from the instructions, it seems I would need system administrator privileges to install NVTX for a CUDA based build. Which is not a possibility for me on a huge shared server with no virtualisation. Are you aware of a repository which might provide precompiled distributions for 11.2? Alternatively, do you know if CUDA 11.0 compiled torch is (by and large) compatible with 11.2 drivers?
Thanks a lot!
No, I’m not aware of pre-built binaries using the latest PyTorch release with CUDA 11.2.
Yes, CUDA11.x drivers are all compatible. In your use case you are depending on backwards compatibility, which should just work. CUDA 11 introduced minor version compatibility, which also allows forward compatibility in 11.x releases.
Thanks! You were right, CUDA 11.1 compiled torch works for my system.
Hi @shape_mismatch ,
How did you get torch for 11.1 CUDA?
Hi. You can find all previous binaries on this page - Previous PyTorch Versions | PyTorch
You could do a search for “11.1” there and you’ll find it.