-
Notifications
You must be signed in to change notification settings - Fork 221
[Transform] Spinquant R3 #1778
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?
[Transform] Spinquant R3 #1778
Conversation
👋 Hi! Thank you for contributing to llm-compressor. Please add the ready label when the PR is ready for review. Note: This is required to complete the testing suite, please only add the label once the PR is code complete and local testing has been performed. |
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 @kylesayrs, 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 enables R3 rotation support for Spinquant, primarily focusing on KV-cache quantization. It achieves this by refactoring the head dimension inference logic into a dedicated utility method and introducing a new attention target within the Spinquant mapping system. The changes facilitate the application of R3 schemes to relevant attention components, and the coherence of a Llama 8B model was tested to validate the implementation.
Highlights
- Spinquant R3 Support: This PR introduces support for the R3 rotation scheme within Spinquant, specifically enabling KV-cache quantization without attention quantization.
- Head Dimension Inference Refactoring: The logic for inferring the head dimension has been extracted into a dedicated private method (
_infer_head_dim
) to improve code organization and reusability across different rotation schemes. - Attention Target Mapping: A new
attn
target has been added to theSpinQuantMapping
to specifically target theself_attn
module, which is utilized by the new R3 scheme forq_attn
andk_cache
locations.
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 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
-
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 adds support for SpinQuant R3 rotations and also implements R4. The refactoring to centralize head dimension inference is a good improvement. I've found a critical issue in the implementation of the R4 scheme where it seems to be applying an identity transformation, making it ineffective. I've also suggested a minor improvement to an error message for better debuggability. Please see the detailed comments.
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.
looks good!
The base branch was changed.
Signed-off-by: Kyle Sayers <[email protected]>
7e6ea83
to
642af14
Compare
Purpose
Prerequisites
Changes
Testing