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Update README.md (#31)
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haozha111 authored Jun 5, 2024
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## High-Level function boundary for performance
We introduce High-Level Function Boundary (HLFB) as a way of annotating performance-critical pieces of the model (e.g. `scaled_dot_product_attention`, or `KVCache`). HLFB allows the converter to lower the annotated blocks to performant TFLite custom ops. Following is an example of applying HLFB to `SDPA`:
https://github.com/google-ai-edge/ai-edge-torch/blob/853301630f2b2455bd2e2f73d8a47e1a1534c91c/ai_edge_torch/generative/layers/attention.py#L74-L122
https://github.com/google-ai-edge/ai-edge-torch/blob/25c764ad21e6f1fda5600dfc27406ef0424c8c3a/ai_edge_torch/generative/layers/scaled_dot_product_attention.py#L69-L117

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