josmi9966:

But why would I want to e.g. choose the cuda 8.0
over the cuda 9.0 version there?


Might be useful if you have an older card that doesn’t support CUDA 9.0 via its drivers, yet.

could I simply always install the version with most recent cuda (9.1 currently) and be happy?

If you never use cuda, I would just install the CPU version, because it’s smaller. Otherwise, just install CUDA 9.1. By default, PyTorch runs always on CPU. If you have the CUDA version, and a supported graphics card, you would e.g., call model.cuda() in your code to enable training using CUDA. Personally, I add the following to my scripts
    if torch.cuda.is_available():
        model = model.cuda()

And for the training Variables:
    if torch.cuda.is_available():
        x, y = x.cuda(), y.cuda()


Originally I thought I have to choose the cuda version I have installed on my system, but since this is not the case, why do I have to choose at all?

You don’t have to choose your system’s CUDA version; it’s only used if you install PyTorch from source. The reason why you want to choose different CUDA versions for the binaries is e.g., for graphics card compatibility