+ runnable
                  + " with executor "
                  + executor,
              e);
    }
  }

  private static final class RunnableExecutorPair {
    final Runnable runnable;
    final Executor executor;
    @CheckForNull RunnableExecutorPair next;

    RunnableExecutorPair(
        Runnable runnable, Executor executor, @CheckForNull RunnableExecutorPair next) {

   * (unless the executor has been shutdown).
   *
   * <p>The returned executor is backed by the executor returned by {@link
   * MoreExecutors#newDirectExecutorService} and subject to the same constraints.
   *
   * <p>Although all tasks are immediately executed in the thread that submitted the task, this

 * {@link #shutDown} and also a {@link #runOneIteration} method that will be executed periodically.
 *
 * <p>This class uses the {@link ScheduledExecutorService} returned from {@link #executor} to run
 * the {@link #startUp} and {@link #shutDown} methods and also uses that service to schedule the
 * {@link #runOneIteration} that will be executed periodically as specified by its {@link

      final Runnable runnable;
      final Executor executor;

      RunnableExecutorPair(Runnable runnable, Executor executor) {
        this.runnable = runnable;
        this.executor = executor;
      }

      void execute() {
        try {
          executor.execute(runnable);
        } catch (RuntimeException e) {
          log.log(
              Level.SEVERE,
              "RuntimeException while executing runnable "

/**
 * Policy on when async requests are executed.
 *
 * Each dispatcher uses an [ExecutorService] to run calls internally. If you supply your own
 * executor, it should be able to run [the configured maximum][maxRequests] number of calls
 * concurrently.
 */
class Dispatcher() {
  internal val lock: ReentrantLock = ReentrantLock()

  /**
   * The maximum number of requests to execute concurrently. Above this requests queue in memory,

  explicit TFE_Executor(tensorflow::EagerExecutor* executor)
      : owned_executor(nullptr), unowned_executor(executor) {}

  tensorflow::EagerExecutor* executor() {
    return owned_executor == nullptr ? unowned_executor : owned_executor.get();
  }

  std::unique_ptr<tensorflow::EagerExecutor> owned_executor;
  tensorflow::EagerExecutor* unowned_executor;
};

    assertEquals(0, numCalls.get());
    reject.set(false);
    executor.execute(task);
    assertEquals(1, numCalls.get());
  }

  /*
   * Under Android, MyError propagates up and fails the test?
   *
   * TODO(b/218700094): Does this matter to prod users, or is it just a feature of our testing

   */
  public static <V extends @Nullable Object> ListenableFuture<V> listenInPoolThread(
      Future<V> future, Executor executor) {
    checkNotNull(executor);
    if (future instanceof ListenableFuture) {
      return (ListenableFuture<V>) future;
    }
    return new ListenableFutureAdapter<>(future, executor);
  }

  /**
   * An adapter to turn a {@link Future} into a {@link ListenableFuture}. This will wait on the

    }

    eventListener.canceled(this)
  }

  override fun isCanceled(): Boolean = canceled

  override fun execute(): Response {
    check(executed.compareAndSet(false, true)) { "Already Executed" }

    timeout.enter()
    callStart()
    try {
      client.dispatcher.executed(this)
      return getResponseWithInterceptorChain()
    } finally {
      client.dispatcher.finished(this)
    }
  }

    ExecutorService executor = newDirectExecutorService();
    assertEquals(ImmutableList.of(), executor.shutdownNow());
    assertTrue(executor.isShutdown());
  }

  public void testExecuteAfterShutdown() {
    ExecutorService executor = newDirectExecutorService();
    executor.shutdown();
    assertThrows(RejectedExecutionException.class, () -> executor.execute(EMPTY_RUNNABLE));
  }