assertThat(record.getMessage())
        .contains("Service FailRunService [FAILED] has failed in the RUNNING state");
  }

  /**
   * Tests that a ServiceManager can be fully shut down if one of its failure listeners is slow or
   * even permanently blocked.
   */
  public void testListenerDeadlock() throws InterruptedException {
    CountDownLatch failEnter = new CountDownLatch(1);

		leafErr = uerr
		// continue to look for leaf errors underneath
		uerr = errors.Unwrap(leafErr)
		depth++
		if depth == unwrapErrsDepth {
			// If we have reached enough depth we
			// do not further recurse down, this
			// is done to avoid any unnecessary
			// latencies this might bring.
			break
		}
	}
	if uerr == nil {
		leafErr = err
	}
	return leafErr
}

// One log message per error.

if [ "${val}" != "val1" ]; then
	echo "expected bucket tag to have replicated, exiting..."
	exit_1
fi
# stop minio1
kill -9 ${site1_pid}
# Update tag on minio2/newbucket when minio1 is down
./mc tag set minio2/newbucket "key=val2"
# create a new bucket on minio2. This should replicate to minio1 after it comes online.
./mc mb minio2/newbucket2

If synchronous replication is configured above, replication is attempted right away prior to returning the PUT object response. In the event that the replication target is down, the `X-Amz-Replication-Status` is marked as `FAILED` and resynced with target when the scanner runs again.

        users indicates that they really appreciate Guava's high power-to-weight ratio. It's
        important to us to keep Guava as easy to use and understand as we can. That means boiling
        features down to compact but powerful abstractions, and controlling feature bloat carefully.


        Guava's main yardstick for evaluating proposed features can be summed up as [utility times

                  startUp();
                  notifyStarted();
                  // If stopAsync() is called while starting we may be in the STOPPING state in
                  // which case we should skip right down to shutdown.
                  if (isRunning()) {
                    try {
                      AbstractExecutionThreadService.this.run();
                    } catch (Throwable t) {

      return requiredFrom; // only one thing to choose, so choose it
    }

    // Find the center and round down. The true center is either centerFloor or halfway between
    // centerFloor and centerFloor + 1.
    int centerFloor = (from + to) >>> 1;

    // Do a binary search until we're down to the range of two which encloses centerFloor (unless

    }
    return true;
  }

  @Override
  public final void clear() {
    backingMap.clear();
    size = 0;
  }

  /**
   * Skeleton of per-entry iterators. We could push this down and win a few bytes, but it's complex
   * enough it's not especially worth it.
   */
  abstract class Itr<T extends @Nullable Object> implements Iterator<T> {
    int entryIndex = backingMap.firstIndex();

   * started. Similarly the task will be delayed if the host lacks compute resources.
   *
   * @throws RejectedExecutionException if the queue is shut down and the task is not cancelable.
   */
  fun schedule(
    task: Task,
    delayNanos: Long = 0L,
  ) {
    taskRunner.withLock {
      if (shutdown) {
        if (task.cancelable) {

  if (func) {
    TFE_ContextRemoveFunction(ctx, "MatMulFunction", status);
  }
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server1.release();
  worker_server2.release();