if (state.iterations() >= state.max_iterations && async) {
      TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);
      TFE_ExecutorWaitForAllPendingNodes(executor, status);
      ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
      TFE_DeleteExecutor(executor);
    }
  }
  TFE_DeleteOp(matmul);
  TFE_DeleteTensorHandle(m);
  TFE_DeleteContext(ctx);

    }

    @Override
    public <T> Future<T> submit(Runnable task, T result) {
      throw new UnsupportedOperationException();
    }

    @Override
    public void execute(Runnable command) {
      throw new UnsupportedOperationException();
    }
  }

  }

  /** @since 13.0 */
  @Override
  public final void addListener(Listener listener, Executor executor) {
    listeners.addListener(listener, executor);
  }

  @Override
  public String toString() {
    return getClass().getSimpleName() + " [" + state() + "]";
  }

  /**
   * Attempts to execute all the listeners in {@link #listeners} while not holding the {@link
   * #monitor}.
   */

Only the code prior to and including the `yield` statement is executed before creating a response:

```Python hl_lines="2-4"
{!../../docs_src/dependencies/tutorial007.py!}
```

The yielded value is what is injected into *path operations* and other dependencies:

```Python hl_lines="4"
{!../../docs_src/dependencies/tutorial007.py!}
```

The code following the `yield` statement is executed after the response has been delivered:

* Add an option `disable_eager_executer_streaming_enqueue` to `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior around parallel remote function invocations; when set to `True`, the eager runtime will be allowed to execute multiple function invocations in parallel.

* `tf.constant_initializer`

    List<StringCatcher> catchers = Lists.newCopyOnWriteArrayList();
    List<Future<?>> futures = Lists.newArrayList();
    ExecutorService executor = Executors.newFixedThreadPool(10);
    int numberOfCatchers = 10000;
    for (int i = 0; i < numberOfCatchers; i++) {
      futures.add(executor.submit(new Registrator(bus, catchers)));
    }
    for (int i = 0; i < numberOfCatchers; i++) {
      futures.get(i).get();
    }

    @Inject
    private LegacySupport legacySupport;

    private final Executor executor;

    public DefaultArtifactResolver() {
        int threads = Integer.getInteger("maven.artifact.threads", 5);
        if (threads <= 1) {
            executor = Runnable::run;
        } else {
            executor = new ThreadPoolExecutor(

Em particular, ao executar no **Kubernetes** você provavelmente **não** vai querer usar vários trabalhadores e, em vez disso, executar **um único processo Uvicorn por contêiner**, mas falarei sobre isso mais adiante neste capítulo.

///

## Vários trabalhadores

  TFE_DeleteTensorHandle(h0);
  TFE_DeleteTensorHandle(h1);
  TFE_DeleteTensorHandle(h2);

  TFE_Executor* executor = TFE_ContextGetExecutorForThread(ctx);
  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TFE_ContextRemoveFunction(ctx, "AddVariablesFunction", status);
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  exit 1
fi

# "TFCI_MACOS_BAZEL_TEST_DIR_PATH" specifies the directory that Bazel should use
# when running tests. Each test will be executed in a separate subdirectory
# inside this directory. TF Mac builds need ~150 GB of disk space to be able to
# run all the tests. Since TFCI Mac VMs execute Bazel test commands in a
# partition with insufficient storage, we specify the