Hi,
I don’t think you should focus on that number so much.
Many process/threads are created when you run pytorch and most of them will be fairly idle. And the current device/core where they sit doesn’t mean anything unless they are actually doing something.
In particular, if you check during testing, then I would expect the processes from the testing dataloader to do stuff at the same time and so to be scheduled on different cores.
But the training workers don’t do anything so they will just stay idle whereever they are.
And I expect it to be the oposite during training where the training processes are scheduled on different cores and the test ones idle somwhere.