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Add MobileNetV5 to KerasHub #2399

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@harshaljanjani harshaljanjani commented Sep 13, 2025 •
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The current design integrates well within the Gemma 3n scope. Ready for reviews!

Numerics Matching (Precision: 1e-5)

image

cc: @divyashreepathihalli @mattdangerw

Colab Notebook

Numerics Validation Reproducibility Notebook

  • 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.

Closes #2401.

@github-actions github-actions bot added the Gemma Gemma model specific issues label Sep 13, 2025
@harshaljanjani harshaljanjani changed the title init: Add initial version Add MobileNetV5 to KerasHub Sep 13, 2025
@harshaljanjani harshaljanjani removed the Gemma Gemma model specific issues label Sep 13, 2025
@harshaljanjani harshaljanjani self-assigned this Sep 13, 2025
@github-actions github-actions bot added the Gemma Gemma model specific issues label Sep 13, 2025
@harshaljanjani harshaljanjani added the WIP Pull requests which are work in progress and not ready yet for review. label Sep 13, 2025
@harshaljanjani harshaljanjani marked this pull request as ready for review September 25, 2025 06:55
@harshaljanjani harshaljanjani added kokoro:force-run Runs Tests on GPU and removed WIP Pull requests which are work in progress and not ready yet for review. labels Sep 25, 2025
@kokoro-team kokoro-team removed the kokoro:force-run Runs Tests on GPU label Sep 25, 2025
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harshaljanjani commented Sep 25, 2025 •
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Let's start the review rounds now that the model numerics match within a 1e-5 tolerance and the design integrates with Gemma 3n!!
Note: The JAX-GPU times out, but the MobileNetV5 tests also pass on JAX-GPU.
No errors are related to MobileNetV5.

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Add MobileNetV5 to KerasHub
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