Functionalization

Functionalization is the process by which we remove mutation from autograd graphs in PyTorch, leaving us with a purely functional graph that we can execute in the normal way. Why do we need to do functionalization? What makes it not so easy to do? How do we do it? And how does it compare to mutation removal that you might see in a compiler?

Om Podcasten

The PyTorch Developer Podcast is a place for the PyTorch dev team to do bite sized (10-20 min) topics about all sorts of internal development topics in PyTorch.