Thanks! Indeed, despite the fact that the main goal is to track ML experiments, the approach taken in `mandala` has a lot in common with e.g. time-travel debugging (https://en.wikipedia.org/wiki/Time_travel_debugging).
In reality, there are many similarities between experiment tracking, debugging, and high-level computation graphs - they're all different ways of getting a handle on what a program did when it was ran.
In reality, there are many similarities between experiment tracking, debugging, and high-level computation graphs - they're all different ways of getting a handle on what a program did when it was ran.