-
Notifications
You must be signed in to change notification settings - Fork 3.4k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[Hot Fix] Ensure process_dataloader is called when tpu_cores > 1 to use Parallel DataLoader #6015
Conversation
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
can we get a test for it?
also, edit chlog...?
Codecov Report
@@ Coverage Diff @@
## master #6015 +/- ##
=======================================
- Coverage 90% 90% -0%
=======================================
Files 170 159 -11
Lines 11784 11209 -575
=======================================
- Hits 10664 10140 -524
+ Misses 1120 1069 -51 |
I made an edit to the main post, I think we need to have some benchmark tests for TPUs that ensure that we stay within reasonable limits for speed/accuracy. We test for model change, but would be good to have a general test for catching these regressions |
nice... yeah we need a test for this so we don't regress in the future |
What does this PR do?
There was a regression in speed when using the TPU accelerator. After inspection, we realised that during the accelerator refactor we missed migrating the
process_dataloader
hook to theTrainingTypePlugin
. This meant that we never wrapped the model when TPU cores > 1 in a parallel data-loader. This PR adds the correct logic.A bigger discussion needs to take place in finding these corner cases which would be shown with regression/benchmarking tests. In the interim we should fix this particular error for release.
Before submitting
PR review
Anyone in the community is free to review the PR once the tests have passed.
Before you start reviewing make sure you have read Review guidelines. In short, see the following bullet-list:
Did you have fun?
Make sure you had fun coding 🙃