and conversions to other media types.

      "Work" shall mean the work of authorship, whether in Source or
      Object form, made available under the License, as indicated by a
      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object

      and conversions to other media types.

      "Work" shall mean the work of authorship, whether in Source or
      Object form, made available under the License, as indicated by a
      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object

 * This is for the benefit of container environments that implement code unloading.
 *
 * Most applications should share a process-wide [TaskRunner] and use queues for per-client work.
 */
class TaskRunner(
  val backend: Backend,
  internal val logger: Logger = TaskRunner.logger,
) {
  val lock: ReentrantLock = ReentrantLock()
  val condition: Condition = lock.newCondition()

## Links

-   [GitHub project](https://github.com/google/guava)
-   [Issue tracker: Report a defect or feature request](https://github.com/google/guava/issues/new)
-   [StackOverflow: Ask "how-to" and "why-didn't-it-work" questions](https://stackoverflow.com/questions/ask?tags=guava+java)
-   [guava-announce: Announcements of releases and upcoming significant changes](https://groups.google.com/group/guava-announce)

	// committing to using the same binary/variant (legacy or nft)
	// within all pods as we do on the host.
	//
	// This should be fine, as the host binaries are all we have to work with here anyway,
	// as we are running within a privileged container - and we don't want to take the time to
	// redetect for each pod anyway.
	//
	// Extreme corner case:

    nextTask.start()
    return nextTask
  }

  private interface SerialTask {
    /** Returns true if this task is ready to start. */
    fun isReady() = true

    /** Do this task's work, and then start another, such as by calling [startNextTask]. */
    fun start()
  }

  private object TestThreadSerialTask : SerialTask {
    override fun start() = error("unexpected call")
  }

  /**
   * The runner doesn't hold references to its queues! Otherwise we'd need a mechanism to clean them
   * up when they're no longer needed and that's annoying. Instead the task runner only tracks which
   * queues have work scheduled.
   */
  @Test fun activeQueuesContainsOnlyQueuesWithScheduledTasks() {
    redQueue.execute("task one", 100.µs) {
      // Do nothing.
    }

    blueQueue.execute("task two", 200.µs) {

   *
   * <p>The multimap is not threadsafe when any concurrent operations update the multimap, even if
   * {@code map} and the instances generated by {@code factory} are. Concurrent read operations will
   * work correctly. To allow concurrent update operations, wrap the multimap with a call to {@link
   * #synchronizedMultimap}.
   *
   * <p>Call this method only when the simpler methods {@link ArrayListMultimap#create()}, {@link

    over RPC. This reduces load on the dispatcher, improving performance of
    distributing datasets. For this to work, the dispatcher's `work_dir` must be
    accessible from workers. If the worker fails to read from the `work_dir`, it
    falls back to using RPC for dataset graph transfer.
*   Adds support for a new "distributed_epoch" processing mode. This processing
    mode distributes a dataset across all tf.data workers, instead of having

// If the pointer sent to done is non-nil AND the error
// is either nil or io.EOF the disk is considered good.
// So if unsure if the disk status is ok, return nil as a parameter to done.
// Shadowing will work as long as return error is named: https://go.dev/play/p/sauq86SsTN2
func (p *xlStorageDiskIDCheck) TrackDiskHealth(ctx context.Context, s storageMetric, paths ...string) (c context.Context, done func(*error), err error) {