type_annotation = annotated_args[0]
        fastapi_annotations = [
            arg
            for arg in annotated_args[1:]
            if isinstance(arg, (FieldInfo, params.Depends))
        ]
        fastapi_specific_annotations = [
            arg
            for arg in fastapi_annotations
            if isinstance(arg, (params.Param, params.Body, params.Depends))
        ]
        if fastapi_specific_annotations:

         */
        public int add2(final int arg1, final int arg2) {
            return arg1 + arg2;
        }

        /**
         * @param arg
         * @return Integer
         */
        public Integer echo(final Integer arg) {
            return arg;
        }

        /**
         *
         */
        public void throwException() {
            throw new IllegalStateException("hoge");

      Parameter param = params.get(i);
      Object arg = args.get(i);
      // Use new fresh value generator because 'args' were populated with new fresh generator each.
      // Two newFreshValueGenerator() instances should normally generate equal value sequence.
      Object shouldBeEqualArg = generateDummyArg(param, newFreshValueGenerator());
      if (arg != shouldBeEqualArg
          && Objects.equal(arg, shouldBeEqualArg)

            argumentsToParameters.entries.firstOrNull { (arg, _) ->
                when (arg) {
                    // TODO: better to utilize. See `createArgumentMapping` in [KtFirCallResolver]
                    is FirNamedArgumentExpression, is FirSpreadArgumentExpression ->
                        arg.psi == argumentExpression.parent
                    else ->
                        arg.psi == argumentExpression
                }

                                                  TF_Status* status) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  const tensorflow::Tensor& arg_tensor = cc_ctx->input(index);
  absl::Status cc_status;
  if (arg_tensor.dtype() != tensorflow::DT_RESOURCE) {
    cc_status = absl::InvalidArgumentError(
        absl::StrCat("Trying to obtain resource handle from Input[", index,

  if (!status->status.ok()) return nullptr;

  if (input_index >= op_def->input_arg_size() || input_index < 0) {
    status->status = tensorflow::errors::InvalidArgument(
        input_index, " out of range for ", op_name);
    return nullptr;
  }

  const tensorflow::OpDef_ArgDef& input_arg = op_def->input_arg()[input_index];

  if (input_arg.number_attr().empty()) {
    status->status = tensorflow::errors::NotFound(

                            val resultMap = mutableMapOf<Name, FirExpression>()
                            resolvedArgumentMapping?.entries?.forEach { (arg, param) ->
                                resultMap[param.name] = arg
                            }

                            KtAnnotationApplicationValue(
                                KtAnnotationApplicationWithArgumentsInfo(

  // First create a simple identity function.
  TF_Graph* function_graph = TF_NewGraph();
  TF_OperationDescription* arg_descr =
      TF_NewOperation(function_graph, "Placeholder", "arg");
  TF_SetAttrType(arg_descr, "dtype", TF_INT32);
  TF_Status* status = TF_NewStatus();
  TF_Operation* arg = TF_FinishOperation(arg_descr, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TF_OperationDescription* id_descr =

  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"
      "      }"
      "      output_arg {"
      "        name: 'sum'"
      "        type: DT_FLOAT"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"

  static <C, E extends @Nullable Object, R extends Iterable<E>>
      BiPredicate<C, C> pairwiseOnResultOf(Function<C, R> arg) {
    Equivalence<C> equivalence = Equivalence.equals().<E>pairwise().onResultOf(arg);
    return equivalence::equivalent;
  }