The focus of this release is **compatibility** with Pydantic v1 and v2, to make sure your current apps keep working. Later there will be more focus on refactors, correctness, code improvements, and then **performance** improvements. Some third-party early beta testers that ran benchmarks on the beta releases of FastAPI reported improvements of **2x - 3x**. Which is not bad for just doing `pip install --upgrade fastapi pydantic`. This was not an official benchmark and I didn't check it myself,...

        `_tpu_estimator_embedding.py`. This allows embedding lookup statistics
        gathered at runtime to be used in embedding layer partitioning
        decisions.
*   PluggableDevice
    *   Third-party devices can now connect to TensorFlow as plug-ins through
        [StreamExecutor C API](https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api.md).
        and