benchmark

9c7aacc4 - Log structured logging overhead to dynamo compile (kinda) (#2454)

Log structured logging overhead to dynamo compile (kinda) (#2454) Summary: X-link: https://github.com/pytorch/pytorch/pull/136142 Pull Request resolved: https://github.com/pytorch/benchmark/pull/2454 This adds structured logging overhead at a per compile basis to compilation metrics. To do so, we track the frame_id_frame_compile_id that trace_structured uses to categorize compiles, and use that as the key in our timing table. Implementation notes: - If there's times we call trace_structured without a compile id, the time won't be measured. Not really a good way around that today given the compile id framework of compilation metrics. Strobelight is still the best way to measure on a per job basis. - We don't actually measure the time it takes to log the compilation metrics itself. Fundamentally, it's not possible to log this properly if we're storing the logging number *in* compilation metrics, since there's no way to measure it before we do it(unless we want discrepancies between dynamo_compile and tlparse, which seems suboptimal). Hopefully for a large job, the cost of structured_logging compilation metrics itself is small. - I wanted to use frame_phase_timing here, but there's a bunch of ids to iron out, and I don't really want to deal with that headache. compilation_time_metrics is sort of what I want, but that isn't by frame/compile id, so it's also a bit off. Putting it into torch.logging as a separate thing so logging tracks its own overhead seems fine, though. Reviewed By: oulgen Differential Revision: D62643611 fbshipit-source-id: 9353d1dbb323079e292b9b4786604fc377971e13