Refactor DistributedEmbedding and embedding_utils to streamline table…

[adityagupta1089]

… spec handling and statistics aggregation

[gemini-code-assist]

Summary of Changes

Hello @adityagupta1089, 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 focuses on enhancing the DistributedEmbedding layer and its associated utility functions by streamlining how table specifications are handled and how input statistics are aggregated. The primary goal is to reduce code complexity and improve maintainability by leveraging more functionality directly from the underlying jax_tpu_embedding library, thereby making the process of synchronizing and updating embedding configurations more efficient and robust.

Highlights

• Refactored DistributedEmbedding: The DistributedEmbedding layer now directly utilizes functions from the jax_tpu_embedding.sparsecore.lib.nn.embedding module for retrieving table specifications, simplifying its internal logic.
• Streamlined Statistics Aggregation: The process of aggregating input statistics across devices has been significantly refactored. It now uses a pmax_aggregate function for efficient synchronization and directly updates preprocessing parameters via embedding.update_preprocessing_parameters when statistics change, replacing previous custom logic.
• Simplified embedding_utils: The embedding_utils.py file has been cleaned up by removing redundant functions like InputStatsPerTable, get_stacked_table_stats, and update_stacked_table_stats. Its get_table_specs function now acts as a direct passthrough to the embedding library's equivalent, and other functions have been updated to return the more direct embedding.SparseDenseMatmulInputStats object.

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[gemini-code-assist]

Code Review

This pull request refactors DistributedEmbedding and embedding_utils to better leverage the jax_tpu_embedding library. The changes streamline table spec handling and statistics aggregation by removing custom utility functions and types in favor of their upstream equivalents. This reduces code duplication and improves maintainability. My review includes a suggestion to refactor a loop for checking statistics changes, which also fixes a potential TypeError.