runtime-compile for any GPU with CC >= 8.6). This improves your
   binary's forward compatibility. However, relying on older PTX to
   provide forward compat by runtime-compiling for newer CCs can
   modestly reduce performance on those newer CCs. If you know exact
   CC(s) of the GPUs you want to target, you're always better off
   specifying them individually. For example, if you want your
   extension to run on 8.0 and 8.6, "8.0+PTX" would work functionally
   because it includes PTX that can runtime-compile for 8.6, but "8.0
   8.6" would be better.
Note that while it's possible to include all supported archs, the
   more archs get included the slower the building process will be, as
   it will build a separate kernel image for each arch.
Note that CUDA-11.5 nvcc will hit internal compiler error while
   parsing torch/extension.h on Windows. To workaround the issue, move
   python binding logic to pure C++ file.
Example use:
      #include  at::Tensor