* fails}.
   */
  protected ScheduledExecutorService executor() {
    @WeakOuter
    class ThreadFactoryImpl implements ThreadFactory {
      @Override
      public Thread newThread(Runnable runnable) {
        return MoreExecutors.newThread(serviceName(), runnable);
      }
    }
    final ScheduledExecutorService executor =
        Executors.newSingleThreadScheduledExecutor(new ThreadFactoryImpl());

import java.time.Duration;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.List;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
import java.util.logging.ConsoleHandler;
import java.util.logging.Level;

   * fails}.
   */
  protected ScheduledExecutorService executor() {
    @WeakOuter
    class ThreadFactoryImpl implements ThreadFactory {
      @Override
      public Thread newThread(Runnable runnable) {
        return MoreExecutors.newThread(serviceName(), runnable);
      }
    }
    final ScheduledExecutorService executor =
        Executors.newSingleThreadScheduledExecutor(new ThreadFactoryImpl());

import java.io.IOException
import java.net.HttpURLConnection
import java.net.ProtocolException
import java.util.concurrent.BlockingQueue
import java.util.concurrent.CountDownLatch
import java.util.concurrent.Executors
import java.util.concurrent.LinkedBlockingQueue
import java.util.concurrent.TimeUnit
import kotlin.test.assertFailsWith
import mockwebserver3.MockResponse
import mockwebserver3.MockWebServer

  virtual void EndStep() = 0;

  // Return the Eager Executor for current thread. Please note that Eager
  // Executor is only used in current TF but not in TFRT.
  virtual EagerExecutor& Executor() = 0;
  // Update the Eager Executor for current thread.
  virtual void SetExecutorForThread(EagerExecutor* executor) = 0;

  // Return a list of local tensorflow::Device*.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are

import static com.google.common.truth.Truth.assertThat;
import static java.lang.Long.MAX_VALUE;
import static java.lang.Thread.currentThread;
import static java.util.concurrent.Executors.newCachedThreadPool;
import static java.util.concurrent.TimeUnit.MILLISECONDS;
import static java.util.concurrent.TimeUnit.NANOSECONDS;
import static java.util.concurrent.TimeUnit.SECONDS;

import static com.google.common.truth.Truth.assertThat;
import static java.lang.Long.MAX_VALUE;
import static java.lang.Thread.currentThread;
import static java.util.concurrent.Executors.newCachedThreadPool;
import static java.util.concurrent.TimeUnit.MILLISECONDS;
import static java.util.concurrent.TimeUnit.NANOSECONDS;
import static java.util.concurrent.TimeUnit.SECONDS;

        // Use max-workers=1 to force non-parallel execution and the tasks to run in the specified order
        // (--no-parallel doesn't have an effect with CC, but max-workers should affect both CC and parallel executors)
        args("--max-workers=1")
        return super.withBuildCache()
    }

    /** Synchronization control for AbstractFutures. */
    private final Sync<V> sync = new Sync<V>();

    // The execution list to hold our executors.
    private final ExecutionList executionList = new ExecutionList();

    /** Constructor for use by subclasses. */
    protected OldAbstractFuture() {}

    /*