// CHECK: tf_executor.island wraps "tf._Retval"(%outputs_0) {T = !tf_type.resource, _mlir_name = "func_call", index = 0 : i64} : (tensor<*x!tf_type.resource>) -> ()
    %ctl_1 = _Retval(%test_func_name0) name("func_call") {T = !tf_type.resource, index = 0 : i64} : tensor<*x!tf_type.resource>
    // CHECK: tf_executor.fetch
  }

    TF_RETURN_IF_ERROR(status);
    graph->AddEdge(node, 0, main_node, i);
  }

  // Similarly with return values, create dummy _Retval nodes fed by `node`.
  for (int64_t i = 0, end = result_types.size(); i < end; ++i) {
    Node* node;
    string retval_name = absl::StrCat("_retval", i);
    Status status = NodeBuilder(retval_name, FunctionLibraryDefinition::kRetOp)
                        .Input(main_node, i)

    for (auto input : inputs) {
      TF_RETURN_IF_ERROR(fn_op->AddInput(input));
    }
    int retvals = outputs.size() - null_indices.size();
    std::vector<AbstractTensorHandle*> fn_outputs(retvals);
    TF_RETURN_IF_ERROR(fn_op->Execute(
        absl::Span<AbstractTensorHandle*>(fn_outputs.data(), fn_outputs.size()),
        &retvals));
    int skipped_indices = 0;
    for (int i = 0; i < outputs.size(); i++) {

// CHECK-NEXT:    "tf.IfrtCall"(%arg0, [[ARRAYKEY]]) <{program_id = 6515870160938153680 : i64, variable_arg_indices = [1 : i32]}> {__tpu_compile_metadata_text = "retvals { sharding { } }"} : (tensor<1x3xf32>, tensor<!tf_type.string>) -> tensor<1x1xf32>
// CHECK-NEXT:    return
//
 func.func @serving_default(%arg0: tensor<1x3xf32>) -> tensor<1x1xf32> {

		// start with a generic forbidden error
		retval := admission.NewForbidden(a, errors.New("Not allowed by PodSecurity")).(*apierrors.StatusError)
		// use message/reason/details/code from admission library if populated
		if result.Result != nil {
			if len(result.Result.Message) > 0 {
				retval.ErrStatus.Message = result.Result.Message
			}
			if len(result.Result.Reason) > 0 {
				retval.ErrStatus.Reason = result.Result.Reason
			}

        }
        map.put(key, this);
    }

    public static ArtifactStatus valueOf(String status) {
        ArtifactStatus retVal = null;

        if (status != null) {
            retVal = map.get(status);
        }

        return retVal != null ? retVal : NONE;
    }

    public boolean equals(Object o) {
        if (this == o) {
            return true;
        }

Status TapeOperation::Execute(absl::Span<AbstractTensorHandle*> retvals,
                              int* num_retvals) {
  TF_RETURN_IF_ERROR(parent_op_->Execute(retvals, num_retvals));
  for (int i = 0; i < *num_retvals; i++) {
    // TODO(srbs): Manage refcount of ForwardOperation's inputs/outputs.
    forward_op_.outputs.push_back(retvals[i]);
  }

			}
			retVal = thisVal
		case 3: // match something like aaa[100]
			thisVal := val[match[1]]
			// If it is a list and looking for more down the path
			if thisVal.GetListValue() != nil && len(path) > 1 {
				index, _ := strconv.Atoi(match[2])
				return getConfigValue(path[1:], thisVal.GetListValue().Values[index].GetStructValue().Fields)
			}
			retVal = thisVal
		}
	}
	return retVal
}

      // CHECK-NEXT: }

      tf_executor.fetch %outputs_10#0 : tensor<?x2xi64>
    }
    func.return %0#0 : tensor<?x2xi64>
    // CHECK:      name: "ParseExample/ParseExampleV2"
    // CHECK-NEXT: op: "_Retval"
    // CHECK-NEXT: input: "ParseExample"

  }

  auto a = ops::_Arg(scope.WithOpName("A"), DT_INT32, 0);
  auto b = ops::_Arg(scope.WithOpName("B"), DT_INT32, 1);
  auto c = ops::Add(scope.WithOpName("C"), a, b);
  auto d = ops::_Retval(scope.WithOpName("D"), c, 0);
  TF_RETURN_IF_ERROR(scope.ToGraph(graph.get()));
  return graph;
}

StatusOr<FunctionDef> SampleFuntionAddXY(const std::string& name) {
  TF_ASSIGN_OR_RETURN(auto graph, SampleGraphAddXY());