Lesson 7 in-class chat ✅

Part 1 (2019)
252

[EDIT] with point 5

Thanks Stas.

Until now (and before you do more experiments), I keep in mind 5 things from your great documentation:

  1. learn.purge() removes any of the Learner guts that are no longer needed and reloads the model on GPU, which also helps to reduce memory fragmentation (copy/paste of your text).
  2. Run learn.purge() before any big change in your model training (image size, unfreeze, etc.).
  3. When you run learn.load(), learn.purge() is done by default (no need to run it).
  4. After learn.export(), it is a good practice to run learn.purge().
  5. (soon, a learn.destroy implementation) In order to reclaim GPU memory or after a “CUDA out of memory exception”, run del learn; gc.collect() or learn=None; gc.collect() (they are equivalent codes). Do not forget to reconstruct your learner after (learn = ...).
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