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I'm excited to try this out. I'm doing most of the ML development on my team. I'll iterate on code development and retrain, multiple times over. Oftentimes, my team members will jump in and want to use a trained model to run some downstream analyses. If the library API has changed, or the model architecture has been tweaked, loading the state_dicts of earlier models becomes nearly impossible without checking out old commits. Even then, storing the results and associating them w commit numbers is super annoying.

Thanks for the tool!

Love the donuts on your website!

Very nice and I appreciate you sharing the code as well as motivation on your blog. The code example to save snapshot looks simple. Did I understand correctly that when you reload a snapshot it puts your current directory into the git state corresponding the checkpoint ?

Mostly yes, when you load a snapshot it first saves your current directory (with git stash —-include-untracked) then it puts your current directory in the same state as the checkpoint. (It performs a git fetch followed by a git checkout).

I wrote more about it in the docs:

http://jellyml.com/docs.html#eat

This is exactly the kind of problems I’m trying to fix! Let me know how it works for you!

Thanks!

I save my code and hyper-params in a JSON file in the same folder.