forward_grads.resize(output_tensors.size());
    TF_RETURN_IF_ERROR(ForwardpropFromTape(
        op_type, output_tensors, backward_function_getter,
        backward_function_deleter, in_grads, absl::MakeSpan(forward_grads)));
  } else {
    TF_RETURN_IF_ERROR(
        (*forward_function)(in_grads, &forward_grads, use_batch_));
  }
  for (int i = 0; i < forward_grads.size(); ++i) {
    if (forward_grads[i] != nullptr) {

 * <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSortedMap} forward <i>indiscriminately</i> to
 * the methods of the delegate. For example, overriding {@link #put} alone <i>will not</i> change
 * the behavior of {@link #putAll}, which can lead to unexpected behavior. In this case, you should

 * <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSortedSet} forward <i>indiscriminately</i> to
 * the methods of the delegate. For example, overriding {@link #add} alone <i>will not</i> change
 * the behavior of {@link #addAll}, which can lead to unexpected behavior. In this case, you should

 * more methods to modify the behavior of the backing queue as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingQueue} forward <b>indiscriminately</b> to the
 * methods of the delegate. For example, overriding {@link #add} alone <b>will not</b> change the
 * behavior of {@link #offer} which can lead to unexpected behavior. In this case, you should

 * the <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingSortedMultiset} forward
 * <b>indiscriminately</b> to the methods of the delegate. For example, overriding {@link
 * #add(Object, int)} alone <b>will not</b> change the behavior of {@link #add(Object)}, which can

		ClosePortForwarderOnInterrupt(fw)

		log.Debugf(fmt.Sprintf("port-forward to %s pod ready", flavor))
		openBrowser(fmt.Sprintf(urlFormat, fw.Address()), writer, browser)

		// Wait for stop
		fw.WaitForStop()

		return nil
	}

	return fmt.Errorf("failure running port forward process: %v", err)
}

func ClosePortForwarderOnInterrupt(fw kube.PortForwarder) {
	go func() {

  public void testFrom() {
    Function<String, Integer> forward =
        new Function<String, Integer>() {
          @Override
          public Integer apply(String input) {
            return Integer.parseInt(input);
          }
        };
    Function<Object, String> backward = toStringFunction();

    Converter<String, Number> converter = Converter.<String, Number>from(forward, backward);

            Currency.FRANC, Country.SWITZERLAND);
    EnumBiMap<Currency, Country> bimap = EnumBiMap.create(map);

    // forward map ordered by currency
    assertThat(bimap.keySet())
        .containsExactly(Currency.DOLLAR, Currency.FRANC, Currency.PESO)
        .inOrder();
    // forward map ordered by currency (even for country values)
    assertThat(bimap.values())

            Currency.FRANC, Country.SWITZERLAND);
    EnumBiMap<Currency, Country> bimap = EnumBiMap.create(map);

    // forward map ordered by currency
    assertThat(bimap.keySet())
        .containsExactly(Currency.DOLLAR, Currency.FRANC, Currency.PESO)
        .inOrder();
    // forward map ordered by currency (even for country values)
    assertThat(bimap.values())

Status RunAndMaybeSum(AbstractContext* ctx, Model forward,
                      absl::Span<AbstractTensorHandle* const> inputs,
                      absl::Span<AbstractTensorHandle*> outputs,
                      bool use_function) {
  AbstractTensorHandle* model_outputs[1];

  // Run the model.
  TF_RETURN_IF_ERROR(
      RunModel(forward, ctx, inputs, model_outputs, use_function));