}

def TF_TPURoundRobinOp : TF_Op<"TPURoundRobin", []> {
  let summary = "Round-robin load balancing on TPU cores.";

  let description = [{
A load balancing op that round-robins among TPU cores.

This op round-robins between the integers in [0, NumTPUCoresVisiblePerHost]. It
is useful for interfacing with TensorFlow ops that take as input a TPU core on

## Major Features and Improvements

*   Support for Python3.9 has been added.
*   `tf.data`:
    *   `tf.data` service now supports strict round-robin reads, which is useful
        for synchronous training workloads where example sizes vary. With strict
        round robin reads, users can guarantee that consumers get similar-sized
        examples in the same step.