-
-
Notifications
You must be signed in to change notification settings - Fork 8.3k
[Misc] make get_class check for Executor instead of ExecutorBase #19914
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
base: main
Are you sure you want to change the base?
[Misc] make get_class check for Executor instead of ExecutorBase #19914
Conversation
👋 Hi! Thank you for contributing to the vLLM project. 💬 Join our developer Slack at https://slack.vllm.ai to discuss your PR in #pr-reviews, coordinate on features in #feat- channels, or join special interest groups in #sig- channels. Just a reminder: PRs would not trigger full CI run by default. Instead, it would only run Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging. To run CI, PR reviewers can either: Add 🚀 |
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.
Summary of Changes
Hello @andyxning, 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 introduces a minor but important refinement to the type validation logic within the get_class
function, ensuring that the distributed executor backend is correctly checked against the Executor
class. It also includes a small documentation fix for improved clarity.
Highlights
- Type Validation Refinement: The
get_class
function invllm/v1/executor/abstract.py
has been updated to validate thedistributed_executor_backend
against theExecutor
class instead ofExecutorBase
. This ensures that the type check aligns with the actualExecutor
type thatexecutor_class
is expected to be. - Documentation Correction: A comment on line 33 in
vllm/v1/executor/abstract.py
was corrected to accurately state thatdistributed_executor_backend
is set inParallelConfig.__post_init__
, notVllmConfig.__post_init__
.
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 in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command>
or @gemini-code-assist <command>
. Below is a summary of the supported commands.
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 issue 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 is currently in preview and 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 to provide feedback.
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
-
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. ↩
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.
Code Review
This pull request makes a couple of precise improvements in vllm/v1/executor/abstract.py
:
- It updates the type check for a custom
distributed_executor_backend
to ensure it's a subclass of the V1Executor
, aligning with the function's return type annotation. This enhances type safety. - It corrects a comment to accurately reflect that
distributed_executor_backend
is initialized withinParallelConfig.__post_init__
.
Both changes contribute to better code correctness and clarity. The reasoning provided in the PR description is sound. Good job!
if not issubclass(distributed_executor_backend, Executor): | ||
raise TypeError( | ||
"distributed_executor_backend must be a subclass of " | ||
f"ExecutorBase. Got {distributed_executor_backend}.") | ||
f"Executor. Got {distributed_executor_backend}.") |
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.
This change from ExecutorBase
to Executor
in the issubclass
check is a good refinement.
The get_class
function is type-hinted to return type["Executor"]
(which refers to vllm.v1.executor.abstract.Executor
). By ensuring that a custom distributed_executor_backend
(if it's a type) is a subclass of this V1 Executor
, you're making the type check more precise and consistent with the function's intended return type.
The previous check against ExecutorBase
was broader and could potentially allow an executor type that isn't a V1 Executor
, which might lead to inconsistencies or runtime issues if the caller specifically expects a V1 Executor
's interface.
This improves the type safety and correctness for custom executor configurations.
Signed-off-by: Andy Xie <[email protected]>
688afd2
to
6fdd438
Compare
Essential Elements of an Effective PR Description Checklist
supported_models.md
andexamples
for a new model.Purpose
executor_class
is of typeExecutor
, soget_class
should also validate againstExecutor
instead ofExecutorBase
Test Plan
NA
Test Result
NA
(Optional) Documentation Update