Add Gemma3n

[kanpuriyanawab]

HF Reference

Closes #2320

[gemini-code-assist]

Summary of Changes

Hello @kanpuriyanawab, 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 initiates the integration of the Gemma3n model into the keras_hub repository. It primarily focuses on establishing the core architectural components for both audio encoding and text decoding, which are crucial for the model's multi-modal capabilities. The changes provide the foundational Keras layers necessary to construct the full Gemma3n model, including its unique attention, feed-forward, and normalization mechanisms.

Highlights

• New Model Integration: This pull request introduces the foundational components for the Gemma3n model, laying the groundwork for a multi-modal Causal Language Model within the keras_hub repository.
• Audio Encoder Architecture: A comprehensive audio encoder based on the Conformer architecture has been added. This includes specialized attention mechanisms with relative position embeddings, feed-forward networks, and lightweight convolutions, designed to process audio inputs effectively.
• Advanced Text Decoder Architecture: A sophisticated text decoder has been implemented, featuring novel components such as the 'Learned Augmented Residual Layer (Laurel)' and 'Alternating Updates (AltUp)' blocks. These, along with custom MLP and attention mechanisms, are designed to facilitate complex multimodal fusion and processing.
• Core Utility Components: A custom RMS Normalization layer (Gemma3nRMSNorm) has been introduced, which serves as a fundamental building block used consistently across various Gemma3n model components for stable training.

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Code Review

This pull request introduces the Gemma3n model, including audio encoder, causal LM, layer normalization, and text decoder components. No specific style guide was provided, and no immediate issues requiring comments at the 'medium', 'high', or 'critical' severity levels were identified in the added code.