message: Add PluggableDevice, oneDNN, and ACL changes to the release note.
diff: * `tf.distribute`
  * `tf.distribute.experimental.ParameterServerStrategy` now supports
  training with Keras `Model.fit` when used with `DatasetCreator`.
  +* PluggableDevice
  + * Third-party devices can now connect to TensorFlow
  + [modularly](https://github.com/tensorflow/community/blob/master/rfcs/20190305-modular-tensorflow.md)
  + through [StreamExecutor C API](https://github.com/tensorflow/community/blob/master/rfcs/20200612-stream-executor-c-api.md).
  + and [PluggableDevice](https://github.com/tensorflow/community/blob/master/rfcs/20200624-pluggable-device-for-tensorflow.md) interface.
  + * Add custom ops and kernels through
  + [kernel and op registration C API](https://github.com/tensorflow/community/blob/master/rfcs/20190814-kernel-and-op-registration.md).
  + * Register custom graph optimization passes with
  + [graph optimization C API](https://github.com/tensorflow/community/blob/master/rfcs/20201027-modular-tensorflow-graph-c-api.md).
  +* [oneAPI Deep Neural Network Library (oneDNN)](https://github.com/oneapi-src/oneDNN)
  + CPU performance optimizations from
  + [Intel-optimized TensorFlow](https://software.intel.com/content/www/us/en/develop/articles/intel-optimization-for-tensorflow-installation-guide.html)
  + are now available in the official x86-64 Linux and Windows builds.
  + * They are off by default. Enable them by setting the environment variable
  + `TF_ENABLE_ONEDNN_OPTS=1`.
  + * We do not recommend using them in GPU systems, as they have not been
  + sufficiently tested with GPUs yet.
  ## Bug Fixes and Other Changes
  * Other
  * Adding show_debug_info to mlir.convert_graph_def and
  mlir.convert_function.
  + * Added [Arm Compute Library (ACL)](https://github.com/ARM-software/ComputeLibrary)
  + support to `--config=mkl_aarch64` build.
  ## Thanks to our Contributors
  