Skip to content

refactor: add a check before layer_sharding logging#7186

Merged
wangxiyuan merged 1 commit intovllm-project:mainfrom
pisceskkk:misc
Mar 12, 2026
Merged

refactor: add a check before layer_sharding logging#7186
wangxiyuan merged 1 commit intovllm-project:mainfrom
pisceskkk:misc

Conversation

@pisceskkk
Copy link
Copy Markdown
Contributor

@pisceskkk pisceskkk commented Mar 12, 2026

What this PR does / why we need it?

We should only display this log message when layer_sharding is enabled.

Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
@pisceskkk pisceskkk requested a review from wangxiyuan as a code owner March 12, 2026 03:34
@gemini-code-assist
Copy link
Copy Markdown
Contributor

Summary of Changes

Hello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request refactors the logging behavior for the layer_sharding configuration. It introduces a conditional check to prevent an informational log message from being emitted when layer_sharding is not active, thereby improving log clarity and reducing noise in the console output.

Highlights

  • Conditional Logging: Implemented a conditional check to ensure that the informational log message regarding linear layer sharding is only displayed when the layer_sharding feature is explicitly enabled.

🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console.

Changelog
  • vllm_ascend/ascend_config.py
    • Added an 'if self.layer_sharding:' condition around the logger.info_once call related to linear layer sharding.
Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature Command Description
Code Review /gemini review Performs a code review for the current pull request in its current state.
Pull Request Summary /gemini summary Provides a summary of the current pull request in its current state.
Comment @gemini-code-assist Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help /gemini help Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for GitHub and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

  1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution.

Copy link
Copy Markdown
Contributor

@gemini-code-assist gemini-code-assist bot left a comment

Choose a reason for hiding this comment

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

Code Review

This pull request adds a check to ensure that the log message for layer sharding is only displayed when layer sharding is actually enabled. This is a good refactoring that improves logging clarity by avoiding confusing messages when the feature is not configured. The implementation is correct and I have no further suggestions.

@github-actions
Copy link
Copy Markdown
Contributor

👋 Hi! Thank you for contributing to the vLLM Ascend project. The following points will speed up your PR merge:‌‌

  • A PR should do only one thing, smaller PRs enable faster reviews.
  • Every PR should include unit tests and end-to-end tests ‌to ensure it works and is not broken by other future PRs.
  • Write the commit message by fulfilling the PR description to help reviewer and future developers understand.

If CI fails, you can run linting and testing checks locally according Contributing and Testing.

Copy link
Copy Markdown
Collaborator

@MengqingCao MengqingCao 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 this improvement!

@MengqingCao MengqingCao added ready read for review ready-for-test start test by label for PR labels Mar 12, 2026
@wangxiyuan wangxiyuan merged commit aa0143e into vllm-project:main Mar 12, 2026
68 of 69 checks passed
845473182 pushed a commit to 845473182/vllm-ascend that referenced this pull request Mar 12, 2026
…to qwen3next_graph

* 'main' of https://github.com/vllm-project/vllm-ascend: (88 commits)
  [main][bugfix] Fixed the problem of speculative decoding in FULL mode (vllm-project#7148)
  fixed fia pad logic in graph mode. (vllm-project#7144)
  [Doc] fix DSV3.1 PD configs (vllm-project#7187)
  refactor: add a check before layer_sharding logging (vllm-project#7186)
  [Build] Add support for Ascend950 chip (vllm-project#7151)
  Revert "[CI] fix skiped e2e test when upgrade vllm version  (vllm-project#6654)" (vllm-project#7166)
  [MODELRUNNERV2]fix penality ops (vllm-project#7013)
  [Bugfix][LoRA] Fix the issue when enable LoRA + tp + fully_sharded_loras (vllm-project#6650)
  [KV Pool]get_num_new_matched_tokens return 0 if token length < block_size (vllm-project#7146)
  [CI] Build Image for v0.16.0rc1 (vllm-project#7155)
  [CI] Skip `test_mooncake_layerwise_connector.py` in `ut` (vllm-project#7147)
  [BugFix]Fix recomputed scheduler bug (vllm-project#7137)
  [Model] Support Minimax-m2.5 on NPU (vllm-project#7105)
  [P/D]Mooncake Layerwise Connector supports hybrid attention manager with multiple kvcache groups (vllm-project#7022)
  Add patch_qwen3_5 for triton ops fused_recurrent_gated_delta_rule (vllm-project#7109)
  [Doc][ReleaseNote] Add release notes for v0.16.0rc1 (vllm-project#7067)
  [Misc] Download on both hk and guiyang region (vllm-project#7129)
  [bugdix] The problem that the w4a8 weight fails to be loaded when the EP is not enabled is resolved. (vllm-project#7090)
  [eagle][cp] fix eagle_cp enable bug2 (vllm-project#7079)
  [CI]Upgrade niglty multi-node-tests max-parallel to 2 (vllm-project#7035)
  ...
Nagisa125 pushed a commit to starmountain1997/vllm-ascend that referenced this pull request Mar 17, 2026
### What this PR does / why we need it?
We should only display this log message when layer_sharding is enabled.
- vLLM version: v0.16.0
- vLLM main:
vllm-project/vllm@4034c3d

Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

module:core ready read for review ready-for-test start test by label for PR

Projects

None yet

Development

Successfully merging this pull request may close these issues.

3 participants