Open notonlyvandalzzz opened 3 years ago
Hi @notonlyvandalzzz ,
our callbacks (like the lr monitor) only make use of our internal logging API. So when you create an MlFlow logger and pass it to the trainer, everything should work as expected.
However, this is the only logging API we offer, since there are various APIs from different logging services and they all integrate differently.
Best, Justus
Oh, that makes sense Could you please update docs regarding internal/external logging borders, manual switches and so on, to make that part of documentation clear?
Would you mind sending a PR to make sure it's clear from your side? So that we definitely know that this has been addressed in a way that helps understanding here?
🐛 Bug
P-L doesn't send lr data to MLFlow when mlflow.pytorch.autolog is enabled and LearningRateMonitor callback activated
To Reproduce
Expected behavior
Dedicated log object inside MLFlow' current run
Environment
Additional context
Was able to override it via this trick: