The immediate benefit is that "what commit produced my last good result" is a local problem, so a local solution is faster and more convenient than a round-trip to an API.
But more broadly, storing data locally makes it easy for others to build tools on top of the data. E.g. a visualisation tool that plots hyperparameters vs metrics, by parsing the metadata from `logis` commits.
Also scientists often don't commit regularly, so there is an opportunity to hijack the commit log for their benefit. Every cycle of edit->run-experiment is an iteration of the scientific method, and capturing that automatically is arguably more valuable than sporadic commits with "stuff" as the message.
Looks really useful! What's the advantage of having this done locally, aside from being free and not requiring a subscription?
Thank you!
The immediate benefit is that "what commit produced my last good result" is a local problem, so a local solution is faster and more convenient than a round-trip to an API.
But more broadly, storing data locally makes it easy for others to build tools on top of the data. E.g. a visualisation tool that plots hyperparameters vs metrics, by parsing the metadata from `logis` commits.
Also scientists often don't commit regularly, so there is an opportunity to hijack the commit log for their benefit. Every cycle of edit->run-experiment is an iteration of the scientific method, and capturing that automatically is arguably more valuable than sporadic commits with "stuff" as the message.
looks useful