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While for optimizations like pad_mm, there are always only two possible choices, for other decision procedures, like kernel choice selection, the set of "available" choices depends on the input. Instead of storing the choices as metadata, we can instead take a look at all choices for which we have collected data (i.e. `df[CHOICE_COL].unique()`). In this PR, I also try to replace "choice" and "feedback" with global constants CHOICE_COL and FEEDBACK_COL. Pull Request resolved: https://github.com/pytorch/pytorch/pull/130304 Approved by: https://github.com/eellison