You can use the get_env_info() function from the torch.utils.collect_env module to get some informations.
To be sure what is used, the best way is to open python. import torch. Copy the path to the main c library with torch._C.__file__. Then in your terminal, run ldd path_to_that_library. It will list the shared libraries it links to.
In my case, for the source install, there is the line: libopenblas.so.0 => MY_OPENBLAS_INSTALL_PATH/lib/libopenblas.so.0. So this one definitely use my own openblas install.
For the binary install, no such line exist, but if you check libtorch.so, it jumps from 95MB in a source install to 230MB for a binary one. That’s because the mkl library is statically linked into it. You can see this by first getting the path to libtorch.so from the ldd command above, then run nm -gC path_to_libtorch.so | grep mkl to see all the symbols associated with mkl (there is a lot of them, this will spam heavily your terminal).
Note that running that same command on the libtorch.so from the source install does not see any mkl symbols (only mkldnn ones that are unrelated).
Now if both your computers are using the mkl library, maybe there is different handling of mac machines in mkl?