-
Notifications
You must be signed in to change notification settings - Fork 45
Add tinker backend. #448
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?
Add tinker backend. #448
Conversation
Summary of ChangesHello @chenyushuo, 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 comprehensive integration of a new 'tinker' backend into the system. It extends the framework's capabilities to support Tinker models for both inference and training, complete with dedicated configuration, model handling, and training wrappers. The changes also involve significant refactoring to enable asynchronous operations and ensure proper synchronization and checkpointing mechanisms are in place for the new backend. Highlights
🧠 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. 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.
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 introduces two major changes. First, it refactors the module registration mechanism, moving from a decorator-based approach to a centralized default_mapping in __init__.py files. This is a significant improvement for code clarity and maintainability. Second, it adds a new "tinker" backend, which is a substantial piece of work but appears to be in a work-in-progress state. My review focuses on the new tinker backend implementation and some general observations. I've identified a critical issue in the new tinker trainer that will cause a crash, along with a few other areas for improvement.
2. fix dyn sync in trainer and explorer 3. fix entropy in tinker trainer 4. add `tinker_base_model` to `InferenceModelConfig`
|
/unittest-all |
|
/unittest-all |
Summary
Failed Tests
Skipped
Tests
Github Test Reporter by CTRF 💚 |
|
/unittest-all |
|
/unittest-explorer |
Summary
Failed Tests
Skipped
Tests
Github Test Reporter by CTRF 💚 |
|
/unittest-module-buffer |
|
/unittest-module-trainer |
Summary
Tests
Github Test Reporter by CTRF 💚 |
Summary
Skipped
Tests
Github Test Reporter by CTRF 💚 |
|
/unittest-all |
|
/gemini review |
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 introduces a new tinker backend, which enables model training on devices without GPUs. This is a significant addition and involves substantial refactoring of the data pipeline, particularly around how experiences are handled (List[Experience] instead of the Experiences batch class). The changes include new configuration options, a TinkerModel for inference, a TinkerTrainerWrapper for training, and updates to documentation and examples. The implementation looks solid, but I've found a critical bug in file handling within the new trainer and a couple of medium-severity issues related to configuration clarity and code maintainability. Overall, great work on adding this new capability.
|
/unittest-module-explorer |
|
/unittest-module-trainer |
|
/unittest-module-algorithm |
|
/unittest-module-buffer |
|
/unittest-module-cli |
|
/unittest-module-common |
Summary
Tests
Github Test Reporter by CTRF 💚 |
Summary
Failed Tests
Skipped
Tests
Github Test Reporter by CTRF 💚 |
|
/unittest-module-trainer |
Description
Experiencesfield in the return value ofSampleStrategytoList[Experience], and update all related interfaces accordingly.Checklist
Please check the following items before code is ready to be reviewed.