Hi!
I created a (several) losses by inheriting from nn.Module. The forward() method accepts predictions and targets. I added them to Learner ( metrics=[] parameter) and everything works decent. (Oh, I created them in this way because a linear combination of those losses act as an actual derivable loss)
I noticed that at the output I have sth like:
epoch train_loss valid_loss None None None time
0 0.980436 1.023589 3.743178 0.343692 0.343692 00:14
1 11.154904 29.588293 146.756012 0.296344 0.296344 00:14
Now, those None in the names weren’t a problem until I wanted to have SaveModelCallback watching the 2’nd (or 3rd) metric. Afaik the SaveModelCallback accepts only named features.
I tried: * Inheriting from Metric too, I got some NotImplemented Exceptions, * writting by hand a .name parameter, * calling mk_metric(myLoss( . . .)) and adding that to metrics constructor parameter, and nothing worked.
My model and targets are of course non trivial so I need to do some tensor acrobatics before feeding them into classical F.mse_loss()
Close to re-implementing everything as a callback, what can I do? My goal is to make SaveModelCallback keep track of the n’th metric, I don’t really care about pretty printing the progress table. So either solution (adding a name to metric or specifying an index to SaveModel) is fine.
p.s. The https://docs.fast.ai/metrics.html#Creating-your-own-metric link is “dead”, that is the #Creating-your-own-metric tag does not exist (3 Jan 2021).
Thank you and I hope I didn’t miss sth obvious on the forum/doc.fastai. But I’ve searched . . .