This podcast goes over the basics of unbacked SymInts. You might want to listen to this one before listening to https://pytorch-dev-podcast.simplecast.com/episodes/zero-one-specialization Some questions we answer (h/t from Gregory Chanan):

- Are unbacked symints only for export?  Because otherwise I could just break / wait for the actual size.  But maybe I can save some retracing / graph breaks perf if I have them too?  So the correct statement is "primarily" for export?

- Why am I looking into the broadcasting code at all?  Naively, I would expect the export graph to be just a list of ATen ops strung together.  Why do I recurse that far down?  Why can't I annotate DONT_TRACE_ME_BRO?

- How does 0/1 specialization fit into this?  I understand we may want to 0/1 specialize in a dynamic shape regime in "eager" mode (is there a better term?), but that doesn't seem to matter for export?

- So far we've mainly been talking about how to handle our own library code.  There is a worry about pushing complicated constraints downstream, similar to torchscript.  What constraints does this actually push?