import static com.google.common.math.ReflectionFreeAssertThrows.assertThrows;
import static com.google.common.truth.Truth.assertThat;
import static java.math.RoundingMode.CEILING;
import static java.math.RoundingMode.DOWN;
import static java.math.RoundingMode.FLOOR;
import static java.math.RoundingMode.HALF_DOWN;
import static java.math.RoundingMode.HALF_EVEN;
import static java.math.RoundingMode.HALF_UP;

   * a {@link MoveDesc}. The first one is the element that was previously at the end of the heap and
   * is now at some position before {@code index}. The second element is the one that was swapped
   * down to replace the element at {@code index}. This fact is used by iterator.remove so as to
   * visit elements during a traversal once and only once.
   */
  @CanIgnoreReturnValue

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

    }
    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();

  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();

  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()

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

  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. */

       * finalizable references could be enqueued subsequently (at which point the class loader
       * would be resurrected by virtue of us having a strong reference to it), we should pretty
       * much just shut down and make sure we don't keep it alive any longer than necessary.
       */
      return null;
    }
    try {
      return finalizableReferenceClass.getMethod("finalizeReferent");