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Adds multiprocessing support for q_learning experiment.

Open Farga83 opened this issue 5 years ago • 4 comments

This adds a process pool for executing the q_learning parameter search in parallel. I found that the process pool performed better than a thread pool which is why I went that route.

This is pretty crude, but I wanted to get it up so others can look at it and use it if they want to speed up a4 runs.

Farga83 avatar Apr 09 '19 01:04 Farga83

@"Jeremy Brown" in ml class if anyone has questions.

Farga83 avatar Apr 09 '19 01:04 Farga83

Wrong @jeremy btw.

On Mon, Apr 8, 2019 at 18:25 Farga83 [email protected] wrote:

@jeremy https://github.com/jeremy Brown if anyone has questions.

— You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub https://github.com/cmaron/CS-7641-assignments/pull/20#issuecomment-481065746, or mute the thread https://github.com/notifications/unsubscribe-auth/AAAAx4-EIN_Q1BZkOHKDbKtpjSWyc14jks5ve-wWgaJpZM4cjZ-x .

jeremy avatar Apr 09 '19 02:04 jeremy

sorry, should have quoted that. Didn't realize it separated first/last in the mention.

Farga83 avatar Apr 09 '19 02:04 Farga83

This could cause more harm than good for most folks. It will use all your ram due to q-learner stats collection if you are not careful. For that reason, I'd probably not merge it in as is, but perhaps keep the pr open for folks inclined to work through any issues they find.

Only tested on Ubuntu 18.04 native, 32 GB ram, python 3.6.8

Farga83 avatar Apr 09 '19 03:04 Farga83