setUp(protocol)
    server.enqueue(MockResponse(body = "A"))
    server.enqueue(MockResponse(body = "A"))
    val executor = Executors.newCachedThreadPool(threadFactory("HttpOverHttp2Test"))
    val countDownLatch = CountDownLatch(2)
    executor.execute(AsyncRequest("/r1", countDownLatch))
    executor.execute(AsyncRequest("/r2", countDownLatch))
    countDownLatch.await()
    assertThat(server.takeRequest().exchangeIndex).isEqualTo(0)

 * <li>{@link #normalizer} - Normalizer.
 * <li>{@link #analyzer} - Suggest analyzer.
 * <li>{@link #contentsParser} - Contents parser.
 * <li>{@link #suggestWriter} - Suggest writer.
 * <li>{@link #threadPool} - Executor service for thread pool.
 * </ul>
 */
public class SuggestIndexer {
    private final static Logger logger = LogManager.getLogger(SuggestIndexer.class);

    /** The suggest analyzer. */

        String result = suggestJob.execute();

        assertTrue(result.contains("Session Id: " + existingSessionId));
        assertEquals(existingSessionId, suggestJob.sessionId);
    }

    // Test execute method with job executor shutdown listener
    public void test_execute_withJobExecutor() {
        createRequiredDirectories();
        MockJobExecutor mockJobExecutor = new MockJobExecutor();

# END TF TEST SUITE OPTIONS

# START CROSS-COMPILE CONFIGS
# Set execution platform to Linux x86
# Note: Lot of the "host_" flags such as "host_cpu" and "host_crosstool_top"
# flags seem to be actually used to specify the execution platform details. It
# seems it is this way because these flags are old and predate the distinction
# between host and execution platform.
build:cross_compile_base --config=clang_local

    visibility = ["//visibility:public"],
    win_def_file = ":tensorflow_filtered_def_file",
)

# To avoid duplication, check that the C++ or python library does not depend on
# the stream executor cuda plugins. Targets that want to use cuda APIs should
# instead depend on the dummy plugins in //tensorflow/compiler/xla/tsl/platform/default/build_config
# and use header only targets.

 * href="https://www.javadoc.io/doc/com.github.ben-manes.caffeine/caffeine/latest/com.github.benmanes.caffeine/com/github/benmanes/caffeine/cache/AsyncCacheLoader.html#asyncLoad(K,java.util.concurrent.Executor)">{@code
 * AsyncCacheLoader.asyncLoad}</a> must return a {@code CompletableFuture}. Users of Guava's {@link
 * com.google.common.util.concurrent.ListenableFuture} can adapt between the two {@code Future}

        .body("def")
        .throttleBody(1, 750, TimeUnit.MILLISECONDS)
        .build(),
    )
    val call = client.newCall(Request(server.url("/a")))
    val executor = Executors.newSingleThreadExecutor()
    val result = executor.submit<Response?> { call.execute() }
    Thread.sleep(100) // wait for it to go in flight.
    call.cancel()
    assertFailsWith<IOException> {
      result.get()!!.body.bytes()
    }

 *     .build();
 * Response response = eagerClient.newCall(request).execute();
 * ```
 *
 * ## Shutdown Isn't Necessary
 *
 * The threads and connections that are held will be released automatically if they remain idle. But
 * if you are writing a application that needs to aggressively release unused resources you may do
 * so.
 *
 * Shutdown the dispatcher's executor service with [shutdown()][ExecutorService.shutdown]. This will

        result = jobExecutor.execute("test", "script with\ttab");
        assertEquals("Executed: test script with\ttab", result);

        result = jobExecutor.execute("test", "script with \"quotes\"");
        assertEquals("Executed: test script with \"quotes\"", result);

        result = jobExecutor.execute("test", "script with 'single quotes'");
        assertEquals("Executed: test script with 'single quotes'", result);

programs that TensorFlow executes. TensorFlow programs are encoded as
computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a