Closed CarloLucibello closed 4 years ago
wait, actually this avoids logging
trainer = Trainer(logger=False, checkpoint_callback=False)
If checkpoint_callback
is not set, a checkpoints
folder is created in the root directory.
Two suggestions:
None
value in addition (or as an alternative) to False
. It seems more natural to me and the first thing I attempted. logger=False
should also trigger checkpoint_callback=False
.If there is no support for these suggestions the issue can ble closed.
Setting logger=False should also trigger checkpoint_callback=False.
Maybe not. The user may want to save checkpoints but no logging turned on. The logger is for experiment tracking (loss curves and other visualizations) and independent of checkpointing.
I may be wrong, but I see no way to entirely avoid logging during training, which sometimes may be convenient for quick exploratory experiments.
I suggest to have
construct a trainer that does no logging at all