class InputList {
 public:
  /// Implicitly convert a list of outputs to a list of inputs. This is useful
  /// to write code such as ops::Concat(ops::Split(x, 4)).
  InputList(const OutputList& out) {  // NOLINT(runtime/explicit)
    for (auto const& x : out) {
      inputs_.push_back(x);
    }
  }

  InputList(

    final ImmutableList<E> inputList;
    final Comparator<? super E> comparator;
    final int size;

    OrderedPermutationCollection(Iterable<E> input, Comparator<? super E> comparator) {
      this.inputList = ImmutableList.sortedCopyOf(comparator, input);
      this.comparator = comparator;
      this.size = calculateSize(inputList, comparator);
    }

    /**

    final ImmutableList<E> inputList;
    final Comparator<? super E> comparator;
    final int size;

    OrderedPermutationCollection(Iterable<E> input, Comparator<? super E> comparator) {
      this.inputList = ImmutableList.sortedCopyOf(comparator, input);
      this.comparator = comparator;
      this.size = calculateSize(inputList, comparator);
    }

    /**

             const TensorShape shape) {
  return Const(scope, Input::Initializer(v, shape));
}

std::vector<NodeBuilder::NodeOut> AsNodeOutList(const Scope& scope,
                                                const InputList& inp);

/// }@

}  // namespace ops
}  // namespace tensorflow

  return NodeBuilder::NodeOut{transformed.node(), transformed.index()};
}

std::vector<NodeBuilder::NodeOut> AsNodeOutList(const Scope& scope,
                                                const InputList& inp) {
  std::vector<NodeBuilder::NodeOut> out;
  for (const auto& i : inp) {
    const auto node_out = AsNodeOut(scope, i);
    if (!scope.ok()) {
      return {};
    }
    out.push_back(node_out);
  }

                  "_1 = ", "tensorflow::ops::Placeholder(scope.WithOpName(\"",
                  arg.name(), "\"), ", type, ");\n");
              strings::StrAppend(
                  out, absl::Substitute("    InputList $0({$0_0, $0_1});\n",
                                        arg.name()));
            } else {
              strings::StrAppend(
                  out, "    auto ", arg.name(), " = ",

    const auto& api_def_arg = *FindInputArg(api_def.arg_order(i), api_def);
    arg_types.push_back(strings::StrCat(
        "::tensorflow::", ArgIsList(arg) ? "InputList" : "Input"));
    arg_names.push_back(AvoidCPPKeywords(api_def_arg.rename_to()));

    // TODO(keveman): Include input type information.
    StringPiece description = api_def_arg.description();

// it is not present.  The new list will be returned.
func setConditionInList(inputList []autoscalingv2.HorizontalPodAutoscalerCondition, conditionType autoscalingv2.HorizontalPodAutoscalerConditionType, status v1.ConditionStatus, reason, message string, args ...interface{}) []autoscalingv2.HorizontalPodAutoscalerCondition {
	resList := inputList
	var existingCond *autoscalingv2.HorizontalPodAutoscalerCondition