- Changed docs for `--contention-profiling` flag to reflect it performed block profiling ([#114490](https://github.com/kubernetes/kubernetes/pull/114490), [@MadhavJivrajani](https://github.com/MadhavJivrajani))

  // PreStop is called immediately before a container is terminated due to an
  // API request or management event such as liveness/startup probe failure,
  // preemption, resource contention, etc. The handler is not called if the
  // container crashes or exits. The Pod's termination grace period countdown begins before the
  // PreStop hook is executed. Regardless of the outcome of the handler, the

        `tf.data.Dataset.enumerate`.
    *   Promoting `tf.data.experimental.unbatch` to core as
        `tf.data.Dataset.unbatch`.
    *   Adds option for introducing slack in the pipeline to reduce CPU
        contention, via `tf.data.Options().experimental_slack = True`
    *   Added experimental support for parallel batching to `batch()` and
        `padded_batch()`. This functionality can be enabled through
        `tf.data.Options()`.