Stop logging during training

[jonasboh]

Feature request

What is the expected behavior?
Train Tabnet without logging epoch, loss etc.

What is motivation or use case for adding/changing the behavior?
I would like to use it in a pipeline with a processbar to show the training state. Loggig the information during training increses the size of the log file and makes it very confusing.

How should this be implemented in your opinion?
Give an option for logging on different level like Info, Warning, Error and let the use decide what gets printed.

Are you willing to work on this yourself?
yes

[Optimox]

I guess you can play with the verbose parameter and set it for example to the maximum number of epochs. This would reduce the training logs to the first and last epochs...

[jonasboh]

Thank you for the suggestion. Unfortunately it is still confusion the log, as I am training quite a few models.
Is there no option to turn the printing completely off?

[Optimox]

I am not sure actually, what happens if you set the verbosity to 0? or -1 ?

[jonasboh]

I set verbosity to 0 and to -1 but always get the first epoch. Is there no way to stop this?

[Optimox]

This comes from the History Callback :

tabnet/pytorch_tabnet/callbacks.py

Line 176 in 2c0c4eb

class History(Callback):

You could change this to remove prints. You would have to change the source code, but it is an easy change.