Lightning-AI/pytorch-lightning

[RFC] Default to infinite epochs, not 1000

Open

#10 343 ouverte le 3 nov. 2021

Voir sur GitHub
 (18 commentaires) (0 réactions) (0 assignés)Python (3 233 forks)batch import
help wantedlet's do it!trainer: argument

Métriques du dépôt

Stars
 (26 687 stars)
Métriques de merge PR
 (Merge moyen 9j 15h) (3 PRs mergées en 30 j)

Description

Currently max_epochs defaults to 1000:

If both max_epochs and max_steps aren't specified, max_epochs will default to 1000. To enable infinite training, set max_epochs = -1.

As a user, though, I would expect that if I don't specify a specific ending point, the training would continue indefinitely. In my own experiments, when the training cut off at 999 epochs, I was confused, and googling the issue didn't readily turn up this line in the documentation. When I checked my logs of all the hyperparams, max_epochs was set to None (I guess this override is applied internally). So as a user I feel like this is bad UX - I can't see a reason to put an arbitrary cutoff versus defaulting to infinite training.

It's especially frustrating when you've invested significant time into a training run, only to have it prematurely cut off due to this unexpected max_epochs limit.

cc @borda

Guide contributeur