Update config from ray cluster#324
Conversation
Summary of ChangesHello @hiyuchang, 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 significantly refines the handling of Ray cluster configurations by introducing dynamic detection capabilities for cluster parameters such as the number of nodes and GPUs per node. This change allows the system to automatically infer these details when they are not explicitly provided, which is particularly beneficial in environments where cluster topology might be dynamic or unknown beforehand. The modifications centralize Ray address management within the configuration object and update related utility functions and test cases to support this more adaptive and robust configuration approach. Highlights
Using Gemini Code AssistThe 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
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 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
|
There was a problem hiding this comment.
Code Review
This pull request introduces a useful feature to automatically detect Ray cluster configurations like node_num and gpu_per_node when they are not explicitly set. The implementation correctly modifies the configuration loading and Ray initialization logic. However, I've identified a few issues that should be addressed. The most critical one is that the new configuration update logic can unexpectedly shut down an existing Ray cluster. Additionally, the new unit test has an external dependency, which is not ideal, and there's some duplicated and non-robust code for detecting GPU configurations. I've provided detailed feedback and suggestions for each of these points.
|
/unittest-module-common |
Summary
Tests
Github Test Reporter by CTRF 💚 |
|
/unittest-module-explorer |
Summary
Tests
Github Test Reporter by CTRF 💚 |
Description
As the title says.
Checklist
Please check the following items before code is ready to be reviewed.