Fix TFP compatibility with Keras 3 (Issue #1945)#2273
Fix TFP compatibility with Keras 3 (Issue #1945)#2273aviralgarg05 wants to merge 2 commits intokeras-team:masterfrom
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Summary of ChangesHello @aviralgarg05, 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 addresses a critical compatibility problem preventing tensorflow_probability from importing correctly in Keras 3 environments. The solution involves a targeted monkey-patch to resolve a missing internal TensorFlow attribute, ensuring seamless integration. Additionally, the changes enhance the robustness of example scripts by preventing their automatic execution when imported, making them more modular and testable. Highlights
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Code Review
This pull request correctly addresses the TFP compatibility issue with a monkey-patch and improves the example scripts by wrapping execution logic in if __name__ == "__main__": guards.
However, there's a critical issue in both examples/generative/vq_vae.py and examples/keras_recipes/bayesian_neural_networks.py. In both files, some of the execution logic that depends on trained models or data splits has been left outside the if __name__ == "__main__": block. This will cause NameError exceptions at runtime because variables defined within the if block are not accessible globally. All top-level execution code needs to be moved inside the main guard to resolve this.
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Pls review @sachinprasadhs |
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Description
This PR addresses Issue #1945, where
tensorflow_probability(TFP) was failing to import in Keras 3 environments due to a missing internal TensorFlow attribute:register_load_context_function.Changes
tf._api.v2.compat.v2.__internal__.register_load_context_functiontoregister_call_context_functionif it's missing. This is a robust workaround for current TFP/Keras 3 version mismatches.if __name__ == "__main__":blocks. This ensures the files can be safely imported by other scripts or test suites without triggering full training runs.examples/generative/vq_vae.pyexamples/generative/real_nvp.pyexamples/keras_recipes/bayesian_neural_networks.pyVerification Results
tensorflow_probabilityand build models without crashing.black.Related Issues
Fixes #1945