Vitalyk/multiturn v2 - #3167
Merged
Merged
Conversation
Contributor
Author
|
/ok to test ee6228e |
6 tasks
daiyaanarfeen
pushed a commit
to daiyaanarfeen/Megatron-LM
that referenced
this pull request
Feb 23, 2026
yangbofun
pushed a commit
to xlm-research/Megatron-LM
that referenced
this pull request
May 22, 2026
terminator123
pushed a commit
to 021ai/Megatron-LM
that referenced
this pull request
Aug 3, 2026
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
What does this PR do?
Why was #2966 reverted?
We failed a gitlab CI test on timings. Every second iteration of the post-change test was extremely fast.
Why did it happen?
This was the configuration of a faulty test:
We sampled 4 rollouts each before and were supposed to consume 2 rollouts per training step (global bs = 2).
Before #2966, sequence packing had a bug which made it sample every iteration no matter on whether we had consumed all the samples or not.
The huge timings you saw in the test were mostly for inference, training step did not take long.
Why didn't it fail on Github CI?
Our github CI used a correct batch size which made it consume all data that was sampled and not being affected by a bug I fixed in #2966.