Hello Peter!
Thanks for your reply.



 ptrblck:

I assume you are referring to the compute capability 3.0, which should work with CUDA6.0 - CUDA10.1.


Indeed.  I was referring to compute capability 3.0 (not that I knew
it at the time …).  Thanks for clearing up that confusion of mine.


If I’m not mistaken, the minimal compute capability for the current binaries is >=3.5,


Do you know how I might determine which compute capability a
binary uses before installing it?
For example, on the main pytorch.org 20 page, in the “QUICK
START LOCALLY” section, one is given the choice of CUDA
9.0 and 10.0 (and none), which I suppose I now understand
to be CUDA SDKs 9.0 and 10.0.  Is there any way for me
deduce whether such a download will support compute
capability 3.0, or whether it starts earliest at 3.5?


However, if you would like to play around with some legacy PyTorch version, you might get lucky finding some supported binaries here (built by @peterjc123).


Thanks for that link.  In a similar vein, do you know how I might
figure out which of these  binaries support which compute capability?
For example, the first file on that google drive is
pytorch_legacy-0.1.12-py35_0.1.12cu80.tar.bz2.
Am I right that the “cu80” part of the file name suggests that the
binary is built with CUDA SDK 8.0 and that it could therefore
potentially support compute capability 2.0 – 6.2?  Is there any
to determine its minimum required compute capability (before
installing)?
(Also am I right that the .tar.bz2 files are linux binaries, while the
.whl file is the sole windows binary?)
Thanks for helping clear these things up for me.
K. Frank