Skip to content

feat: add routing replay for Mcore#2693

Merged
yanring merged 7 commits intoNVIDIA:devfrom
litianjian:autoformatter-dev
Jan 20, 2026
Merged

feat: add routing replay for Mcore#2693
yanring merged 7 commits intoNVIDIA:devfrom
litianjian:autoformatter-dev

Conversation

@litianjian
Copy link
Copy Markdown
Contributor

What does this PR do ?

This PR introduces a "Router Replay" feature for Mixture-of-Experts (MoE) layers. This functionality provides a deterministic routing mechanism, which is essential for debugging, controlled experimentation, and reproducing model behavior.

Inspired by recent approaches in stabilizing MoE models Router Replay(R2) and Rollout Router Replay(R3), RouterReplay implementation allows developers to easily save and set the router's replay information, providing precise control over the expert selection process to mitigate routing inconsistencie

Implementation Details:

  1. Configuration Flag:
  • A new boolean flag, enable_routing_replay , has been added to TransformerConfig . This allows users to enable or disable the feature globally.
  1. RouterReplay Class:
  • A new class, RouterReplay , is introduced in moe_utils.py to manage the state and data for the replay functionality.
  • It operates in three modes, defined by the RoutingMode enum:
    • None : The default state, where standard routing occurs.
    • RECORD : The router records the expert indices ( topk_ids ) for each token.
    • REPLAY : The router bypasses the standard Top-K logic and instead uses the previously recorded expert indices to route tokens.
  1. Integration with TopKRouter :
  • In router.py , the TopKRouter now initializes a RouterReplay instance if config.enable_routing_replay is True .
  • This instance is then passed to the topk_routing_with_score_function during the routing process.
  1. Core Logic in moe_utils.py :
  • The topk_routing_with_score_function has been updated to handle the router_replay object.
  • When the mode is RECORD , it captures the topk_ids after they are computed.
  • When the mode is REPLAY , it retrieves the stored topk_ids from the RouterReplay object and uses them to construct the routing gates and probabilities, effectively bypassing the dynamic routing calculation.

⚠️ For major changes (either in lines of code or in its impact), please make sure to first share discuss a design-doc with the team.

Contribution process

flowchart LR
    A[Pre-checks] --> B[PR Tests]
    subgraph Code Review/Approval
        C1[Expert Review] --> C2[Final Review]
    end
    B --> C1
    C2 --> D[Merge]
Loading

Pre-checks

  • I want this PR in a versioned release and have added the appropriate Milestone (e.g., Core 0.8)
  • I have added relevant unit tests
  • I have added relevant functional tests
  • I have added proper typing to my code Typing guidelines
  • I have added relevant documentation
  • I have run the autoformatter.sh on my PR

Code review

The following process is enforced via the CODEOWNERS file for changes into megatron/core. For changes outside of megatron/core, it is up to the PR author whether or not to tag the Final Reviewer team.

For MRs into `main` branch

(Step 1): Add PR label Expert Review

(Step 2): Collect the expert reviewers reviews

  1. Attach the Expert Review label when your PR is ready for review.
  2. GitHub auto-assigns expert reviewers based on your changes. They will get notified and pick up your PR soon.

⚠️ Only proceed to the next step once all reviewers have approved, merge-conflict are resolved and the CI is passing.
Final Review might get declined if these requirements are not fulfilled.

(Step 3): Final Review

  1. Add Final Review label
  2. GitHub auto-assigns final reviewers based on your changes. They will get notified and pick up your PR soon.

(Optional Step 4): Cherry-pick into release branch

If this PR also needs to be merged into core_r* release branches, after this PR has been merged, select Cherry-pick to open a new PR into the release branch.

For MRs into `dev` branch The proposed review process for `dev` branch is under active discussion.

MRs are mergable after one approval by either eharper@nvidia.com or zijiey@nvidia.com.

Merging your PR

Any member of core-adlr and core-nemo will be able to merge your PR.

@litianjian litianjian requested review from a team as code owners December 17, 2025 12:32
@copy-pr-bot
Copy link
Copy Markdown

copy-pr-bot Bot commented Dec 17, 2025

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

Pull request vetters can view their responsibilities here.

Contributors can view more details about this message here.

@ISEEKYAN
Copy link
Copy Markdown
Contributor

@yanring

Copy link
Copy Markdown
Contributor

@yanring yanring left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks for the great PR👍. I've left a few comments.

Comment thread megatron/core/transformer/transformer_config.py
Comment thread megatron/core/transformer/moe/moe_utils.py Outdated
Comment thread docs/source/api-guide/router_replay.md
Comment thread megatron/core/transformer/moe/moe_utils.py Outdated
Comment thread docs/source/api-guide/router_replay.md Outdated
Comment thread megatron/core/transformer/moe/moe_utils.py Outdated
@yanring yanring requested a review from ISEEKYAN January 7, 2026 06:59
@litianjian
Copy link
Copy Markdown
Contributor Author

Thanks for the great PR👍. I've left a few comments.

I am very honored to receive your reply and suggestions. I will follow your advice to modify the code.

@chtruong814 chtruong814 added the needs-follow-up Issue needs follow-up label Jan 11, 2026
@BestJuly BestJuly added the dev branch Dev branch related issues and development label Jan 12, 2026
@yanring
Copy link
Copy Markdown
Contributor

yanring commented Jan 12, 2026

/ok to test 1a1793d

@copy-pr-bot
Copy link
Copy Markdown

copy-pr-bot Bot commented Jan 12, 2026

/ok to test 1a1793d

@yanring, there was an error processing your request: E2

See the following link for more information: https://docs.gha-runners.nvidia.com/cpr/e/2/

@yanring yanring enabled auto-merge January 12, 2026 07:41
@yanring
Copy link
Copy Markdown
Contributor

yanring commented Jan 12, 2026

/ok to test 745cb8f

auto-merge was automatically disabled January 13, 2026 03:50

Head branch was pushed to by a user without write access

@yanring yanring enabled auto-merge January 13, 2026 13:22
@yanring
Copy link
Copy Markdown
Contributor

yanring commented Jan 13, 2026

/ok to test dbc0158

@github-actions
Copy link
Copy Markdown
Contributor

Thank you for your contribution!

NVIDIA Megatron-LM is currently transitioning to development on Github. We will aim to review your PR after we complete our transition and stabilize our Github development process.

Thank you for your understanding.

@yanring yanring added this pull request to the merge queue Jan 13, 2026
@github-merge-queue github-merge-queue Bot removed this pull request from the merge queue due to no response for status checks Jan 14, 2026
@chtruong814 chtruong814 added the needs-follow-up Issue needs follow-up label Jan 15, 2026
@yanring yanring added this pull request to the merge queue Jan 20, 2026
Merged via the queue into NVIDIA:dev with commit 9ea50a9 Jan 20, 2026
45 of 47 checks passed
@chtruong814 chtruong814 removed the needs-follow-up Issue needs follow-up label Jan 20, 2026
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

community-request dev branch Dev branch related issues and development

Projects

None yet

Development

Successfully merging this pull request may close these issues.

6 participants