Just read this topic today: [Solved] Reproducibility: Where is the randomness coming in?
It mentions how to get reproducible results, but it uses a doc from dev (https://docs.fast.ai/dev/test.html#getting-reproducible-results) where it reads: set num_workers=1 (or 0) in your DataLoader/DataBunch.
From the second lesson and Hirome notes (https://github.com/hiromis/notes/blob/master/Lesson2.md), @jeremy explicit tells to set the seed in order to always get the same validation set, but doesn’t say anything for num_workers.
So, 1) is the num_workers=1 really needed ir order to get the same validation set, or is it just needed when executing the tests?
And 2) Should these be explicited in the basic_data docs, in order to instruct how to get the same dataset for training and validation when needed?
Just a note: I am still learning from the lessons while trying to contribute to the project when I see something that’s missing or confusing in the docs. I hope to contribute more later on as I get more hands on experience.
I also can’t run the tests because I still haven’t got myself a GPU so this restricts me a lot. Is it possible to run them on GCP? How much time is needed for the documentation’s tests?
Thanks!