You can pick any PyTorch tag, which would support your setup (e.g. CUDA9.2). The currently required min. CUDA toolkit version is 10.2, so you should double check if PyTorch 1.6.0 supports 9.2. Yes, the release/1.6 branch is correct. You could alternatively use git checkout v1.6.0.


The different release versions are all tagged in the GitHub repository. I don’t know which VisuaStudio versions are required as I’m not using Windows.


See 2.


Using TORCH_CUDA_ARCH_LIST is correct. The source build will be installed into your current environment if you use python setup.py install and will be usable there. The installed package will be located in your env also. E.g. if you are using conda to manage your environments, you would find the package in e.g. /opt/conda/lib/python3.8/site-packages/torch if you install it in the base environment.


See 4.