Aren't the two lines enough for you? BTW why lightning and not ignite?
Looks like it is still running DeliciousSeaanemone40 , you're suggesting it is slower than usual? There are some messages there that I've never seen before
There are examples but nothing comes to mind when. Thinking about well fleshed out for Bert etc. Maybe someone here can correct me
All should work, again - is it much slower than without trains?
i'm using logging.getLogger, tqdm, maybe it's not supported?
I guess it's not relevant but if it helps:
env settings:
Linux manjaro18 5.4.12-1-MANJARO
Conda env:
Python 3.8.1
torch 1.4
What's your code situation? Is it open enough to allow you to create an issue for this on our GitHub?
If you can recreate the same problem with the original repo... 🤯 🤩
yes I cat see that now ^^'
I'm not sure whether the problem can be recreate in the original BERT repo, but i'll try to look into it. never tried to run the original-repo's model/data.
Not so much relevant, since it can be seen from your task 😄 but it would be interesting to find out if trains made something be much slower, and if so - how
i'm doing plt.savefig for both of the successful uploads and the failed ones.
I think the only difference is the failed ones use the plt.subplots.
Are you doing imshow or savefig? Is this the matplotlib oop or original subplot? Any warning message relevant to this?
Hi, I just checked the two lines concept, didn't managed to get normal run-time (supposed to last a minute but it's not progressing) nor the entire logging..
also, for some reason these kind of images (wide, side-by-side) failed to upload (other formats suceeded):
https://demoapp.trains.allegro.ai/projects/215414aaade846db95a9eaac90a9a2d0/experiments/a967de8bd09145ca9e431d96ebb29345/output/log
emm fortunately not (academic thesis which was not published yet), but I can refer to the https://github.com/codertimo/BERT-pytorch I've based on
But what i meant was an entire project with a well built structure to bases on.. If it uses lightning/ignite/trains for scaling/simplicity reasons - even better (: