Hi,
This does not exist in pytorch.
I think it is unlikely to be added in future releases because of how the cuda allocator that we use works.
Most of the work that we do is actually GPU compute bound. So even if there is extra memory available, there is no point for sometone else to launch a job on the same GPU: running both job at the same time is actually slower than running them one after the other + it has higher memory demand.
I guess the solution is not to share a single GPU if you actually need all of it.