register mobilenet presets

[sachinprasadhs]

Description of the change

Reference

Colab Notebook

Checklist

• I have added all the necessary unit tests for my change.
• I have verified that my change does not break existing code and works with all backends (TensorFlow, JAX, and PyTorch).
• My PR is based on the latest changes of the main branch (if unsure, rebase the code).
• I have followed the Keras Hub Model contribution guidelines in making these changes.
• I have followed the Keras Hub API design guidelines in making these changes.
• I have signed the Contributor License Agreement.

[gemini-code-assist]

Summary of Changes

Hello @sachinprasadhs, 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 integrates new preset configurations for the MobileNetV5 model into Keras Hub, specifically adding a preset for a 300M-parameter vision encoder used with Gemma 3n. This enhancement makes the model more readily usable with pre-defined configurations and enables comprehensive testing of these presets.

Highlights

• MobileNetV5 Presets Registration: The pull request registers new preset configurations for the MobileNetV5 model, making them accessible within the Keras Hub.
• New mobilenetv5_300m_enc_gemma3n Preset: A specific preset, mobilenetv5_300m_enc_gemma3n, is introduced, described as a lightweight 300M-parameter convolutional vision encoder for Gemma 3n.
• Test Unskip: A previously skipped test, test_smallest_preset, in mobilenetv5_backbone_test.py has been enabled, indicating that the necessary presets are now available for testing.

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 by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

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 pull request 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

1. 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. ↩

[gemini-code-assist]

Code Review

This pull request registers a new preset for MobileNetV5, mobilenetv5_300m_enc_gemma3n. The changes include adding the preset definition, registering it, and enabling the corresponding test. My review found an important inconsistency in how this new preset name is used across different files, which will cause tests to fail. Please correct the preset name in the test file and the docstring example to match the definition in mobilenetv5_presets.py.

[laxmareddyp]

LGTM