if (TF_GetCode(status) != TF_OK) return;

  // unwrap op_ and set step_id only if valid step id value was set.
  // Currently only required for non-TFRT use cases, e.g., EagerOp.
  if (step_id_.has_value()) {
    tensorflow::unwrap(op_.get())->SetStepId(step_id_.value());
  }

  TFE_Execute(op_.get(), unwrapped_results.data(), &real_num_outputs, status);
  if (TF_GetCode(status) != TF_OK) {

  DLManagedTensor* dlmt = static_cast<DLManagedTensor*>(dlm);
  DLTensor* dl_tensor = &dlmt->dl_tensor;
  absl::optional<std::string> device_name =
      DeviceNameFromDlContext(dl_tensor->device, status);
  if (!device_name.has_value()) {
    status->status =
        tensorflow::errors::InvalidArgument("Unsupported Device Type");
    return nullptr;
  }
  TF_DataType dtype;
  Status s = TfDataTypeFormDlDataType(dl_tensor->dtype, &dtype);

            comparator);

    return new AbstractIterator<C>() {
      @CheckForNull C lastValue;

      @Override
      @CheckForNull
      protected C computeNext() {
        while (merged.hasNext()) {
          C next = merged.next();
          boolean duplicate = lastValue != null && comparator.compare(next, lastValue) == 0;

          // Keep looping till we find a non-duplicate value.
          if (!duplicate) {

    assertThat(iterable.firstMatch(Predicates.equalTo("cool"))).hasValue("cool");
    assertThat(iterable.firstMatch(Predicates.equalTo("pants"))).hasValue("pants");
    assertThat(iterable.firstMatch(Predicates.alwaysFalse())).isAbsent();
    assertThat(iterable.firstMatch(Predicates.alwaysTrue())).hasValue("cool");
  }

    assertThat(MediaType.parse("text/plain; charset =utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain; charset= utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain; charset = utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain;charset =utf-8").charset()).hasValue(UTF_8);
  }

  public void testGetCharset() {

    assertThat(MediaType.parse("text/plain; charset =utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain; charset= utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain; charset = utf-8").charset()).hasValue(UTF_8);
    assertThat(MediaType.parse("text/plain;charset =utf-8").charset()).hasValue(UTF_8);
  }

  public void testGetCharset() {

        String value = null;
        boolean haveValue = false;
        if (encoding != null) {
            try {
                value = item.getString(encoding);
                haveValue = true;
            } catch (final Exception e) {}
        }
        if (!haveValue) {
            try {
                value = item.getString("ISO-8859-1");

    assertThat(Stream.empty().collect(MoreCollectors.toOptional())).isEmpty();
  }

  public void testToOptionalSingleton() {
    assertThat(Stream.of(1).collect(MoreCollectors.toOptional())).hasValue(1);
  }

  public void testToOptionalNull() {
    Stream<@Nullable Object> stream = Stream.of((Object) null);
    try {
      stream.collect(MoreCollectors.toOptional());
      fail("Expected NullPointerException");

      tensorflow::EvaluateConstantTensorRunner{
          graph->graph.op_registry(),
          graph->graph.versions().producer(),
      });
  if (!status_or.ok() || !status_or->has_value()) {
    *result = nullptr;
    status->status = std::move(status_or).status();
    return false;
  }
  *result = TF_TensorFromTensor(**status_or, &status->status);
  return status->status.ok();
}

        // nothing to do, we must have been cancelled, don't bother inspecting the future.
        return;
      }
      Object valueToSet = getFutureValue(future);
      if (ATOMIC_HELPER.casValue(owner, this, valueToSet)) {
        complete(
            owner,
            /*
             * Interruption doesn't propagate through a SetFuture chain (see getFutureValue), so
             * don't invoke interruptTask.