zzzhhh:

Is it possible that PyTorch is divided into GPU version and non-GPU version and the sys admin happened to install a non-GPU version?


Depending how you’ve installed PyTorch, you can pick between the CPU and CUDA runtimes as described in the install instructions 42.



 zzzhhh:

If so, how can I tell if the PyTorch installed is GPU or non-GPU version?


Check print(torch.version.cuda) as well as python -m torch.utils.collect_env and make sure a CUDA runtime is found.
If that’s the case, your local setup is most likely broken (e.g. via updating an NVIDIA driver without a restart etc.).



 zzzhhh:

Is there any requirements on CUDA version so that CUDA 11.1 installed does not get along well with PyTorch 1.8.0?


Again, it depends on your setup. If you’ve installed the pip wheels or conda binaries with a CUDA runtime, the local CUDA toolkit won’t be used unless you are building a custom CUDA extension, as the binaries already ship with their own CUDA runtime.