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  1. RELEASE.md

            `_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
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  2. .bazelrc

    #     dynamic_kernels:  Try to link all kernels dynamically (experimental).
    #     dbg:              Build with debug info
    #
    # TF version options;
    #     v2: Build TF v2
    #
    # Feature and Third party library support options:
    #     xla:          Build TF with XLA
    #     tpu:          Build TF with TPU support
    #     cuda:         Build with CUDA support.
    #     cuda_clang    Build with CUDA Clang support.
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