Cleanup templates/ dir

[sachinprasadhs]

Ran the python autogen.py make command and noticed many of the tutorials and examples having outdated examples/not synced or having extra length output for epochs.

[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 delivers a comprehensive update and expansion of the examples and tutorials, primarily driven by running the autogen.py make command. The changes aim to enhance clarity, ensure API compatibility with Keras 3, and introduce advanced features like distributed embeddings on TPUs. Several existing tutorials have been streamlined by removing verbose output and correcting minor issues, while new examples showcase cutting-edge capabilities in recommendation systems.

Highlights

• Tutorial Output Cleanup: Removed excessive and outdated output logs from several tutorials (basic_ranking.md, basic_retrieval.md, listwise_ranking.md, sas_rec.md, scann.md, sequential_retrieval.md), making them more concise and readable.
• Keras API Alignment: Updated API calls from tf.keras.Sequential and tf.keras.optimizers.Adagrad to keras.Sequential and keras.optimizers.Adagrad respectively across multiple examples, ensuring compatibility with Keras 3.
• New Distributed Embedding Tutorials: Introduced two new tutorials (distributed_embedding_jax.md and distributed_embedding_tf.md) demonstrating the use of keras_rs.layers.DistributedEmbedding with TPU SparseCore for movie ranking, using both JAX and TensorFlow backends.
• DCN Model Refactoring and Updates: The DCN tutorial (dcn.md) was significantly updated, including refactoring the model definition into a class, adjusting hyperparameters (embedding_dim, projection_dim, learning_rate, num_epochs, batch_size), adding a final dense layer, and updating performance metrics.
• Data Leakage Prevention: Modified the listwise_ranking.md and sequential_retrieval.md tutorials to correctly split train and test data per user, preventing data leakage and ensuring more robust evaluation.
• Wav2Vec2 Audio Classification Tutorial Removal: The wav2vec2_audiocls.md tutorial was removed from the examples.

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[gemini-code-assist]

Code Review

This pull request provides a comprehensive update to the documentation and example files. The changes include removing verbose output from notebooks, fixing typos, adding necessary installation commands, and performing minor but important code refactoring and bug fixes. A new set of tutorials for DistributedEmbedding on JAX and TensorFlow has also been added. Overall, these changes significantly improve the clarity, correctness, and usability of the examples. I've found one minor issue with a leftover terminal artifact in one of the markdown files.

[hertschuh]

What about the ipynb files? Were they all up to date?

[sachinprasadhs]

Noticed that these .md files are actually present in https://github.com/keras-team/keras-io/tree/master/examples/keras_rs, why do we have these again in templates directory?

[sachinprasadhs]

This is the PR which caused this #2083
Was it intentional or accidental?

[hertschuh]

This was an accident, the files in the templates folder should come from autogen and should not be committed in the repo (with some exceptions like index.md). Can you delete them all?

[sachinprasadhs]

Got it, deleted the files under temples/ except index.md files, also updated the .gitignore file.

[hertschuh]

Thanks for the cleanup! This was confusing.