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) {

if [ "${policy}" != "null" ]; then
	echo "expected policy detach to have replicated, exiting..."
	exit_1
fi

kill -9 ${site1_pid1} ${site1_pid2}

# 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

      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();

  fun shutdown() {
    serverSocket!!.close()
    executor.shutdown()
    if (!executor.awaitTermination(5, TimeUnit.SECONDS)) {
      throw IOException("Gave up waiting for executor to shut down")
    }
  }

  private fun service(from: Socket) {
    val name = "SocksProxy ${from.remoteSocketAddress}"
    threadName(name) {
      try {
        val fromSource = from.source().buffer()

        for (Plugin plugin : project.getBuild().getPlugins()) {
            for (PluginExecution execution : plugin.getExecutions()) {
                // if the phase is specified then I don't have to go fetch the plugin yet and pull it down
                // to examine the phase it is associated to.
                String phase = execution.getPhase();
                if (aliases.containsKey(phase)) {
                    phase = aliases.get(phase);

   * 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();

  protected void tearDown() throws Exception {

    // Make sure we have no waiting threads.
    latch.countDown();
  }

  /** Constructs a listenable future with a value available after the latch has counted down. */
  protected abstract <V> ListenableFuture<V> createListenableFuture(
      V value, @Nullable Exception except, CountDownLatch waitOn);

  /** Tests that the {@link Future#get()} method blocks until a value is available. */