Add code snippet for embeddings normalization #13507
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Summary of Changes
Hello @Tengxin-Li, 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 new utility module to the generative_ai/embeddings directory. Its primary purpose is to provide a robust method for normalizing embedding vectors, ensuring their consistent magnitude for downstream machine learning tasks that rely on normalized representations.
Highlights
- New Utility Function: I've added a new Python function,
normalize_embedding, designed to normalize NumPy array embeddings to have an L2 norm (magnitude) of 1. - Numerical Stability: The
normalize_embeddingfunction includes a check to handle cases where the input embedding's magnitude is zero, returning the original array to prevent division by zero errors.
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Code Review
This pull request introduces a new utility function to normalize embeddings. The implementation is clear, but I have a couple of suggestions to improve its robustness and maintainability.
My main concerns are:
- The use of direct floating-point comparison, which can be unreliable.
- The absence of unit tests for the new functionality, which is crucial for ensuring correctness.
Please see my detailed comments in the code. Addressing these points will make the new code more robust and easier to maintain.
Description
Add code snippet for embeddings normalization, so that the magnitude of the array is always 1.
Checklist
nox -s py-3.9(see Test Environment Setup)nox -s lint(see Test Environment Setup)