Status LessThanTenCond(const Scope& s, const std::vector<Output>& inputs,
                       Output* output) {
  *output = ops::Less(s, inputs[0], 10);
  return s.status();
}

Status AddOneBody(const Scope& s, const std::vector<Output>& inputs,
                  std::vector<Output>* outputs) {
  outputs->push_back(ops::Add(s, inputs[0], 1));
  return s.status();
}

      [](const Scope& s, const std::vector<Output>& inputs, Output* output) {
        *output = ops::Less(s, inputs[0], 10);
        return s.status();
      },
      [](const Scope& s, const std::vector<Output>& inputs,
         std::vector<Output>* outputs) {
        outputs->push_back(ops::AddN(s, {inputs[0], inputs[1]}));
        outputs->push_back(ops::AddN(s, {inputs[1], 1}));
        outputs->push_back(inputs[2]);

  explicit CSession(TF_Session* session);

  ~CSession();

  void SetInputs(std::vector<std::pair<TF_Operation*, TF_Tensor*>> inputs);
  void SetOutputs(std::initializer_list<TF_Operation*> outputs);
  void SetOutputs(const std::vector<TF_Output>& outputs);
  void SetTargets(std::initializer_list<TF_Operation*> targets);

  void Run(TF_Status* s);

  void CloseAndDelete(TF_Status* s);

      %outputs_4, %control_5 = tf_executor.island wraps "tf.Range"(%outputs_2, %outputs_0, %outputs) {device = ""} : (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<?xi32>
      %outputs_6, %control_7 = tf_executor.island wraps "tf.Sub"(%outputs_0, %arg0) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
      %outputs_8, %control_9 = tf_executor.island wraps "tf.FloorDiv"(%outputs_6, %outputs) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>

    %outputs_4, %control_4 = tf_executor.island wraps "tf.Identity"(%outputs_3) {T = "tfdtype$DT_FLOAT", device = "", name = "output_0_shard_0"} : (tensor<0xf32>) -> tensor<0xf32>
    %control_5 = tf_executor.island(%control, %control_4) wraps "tf.NoOp"() : () -> ()

      %outputs_18, %control_19 = "tf_executor.island"() ({
        %0 = "tf.Mul"(%outputs_16#0, %outputs_4) {device = ""} : (tensor<*xf32>, tensor<f32>) -> tensor<*xf32>
        "tf_executor.yield"(%0) : (tensor<*xf32>) -> ()
      }) : () -> (tensor<*xf32>, !tf_executor.control)
      %outputs_20, %control_21 = "tf_executor.island"() ({

      %outputs_5, %control_6 = tf_executor.island wraps "tf.PreventGradient"(%outputs_2) {device = "", message = "The jax2tf-converted function does not support gradients. Use `with_gradient` parameter to enable gradients"} : (tensor<2x3xi32>) -> tensor<2x3xi32>
      %outputs_7, %control_8 = tf_executor.island wraps "tf.Identity"(%outputs_5) {device = ""} : (tensor<2x3xi32>) -> tensor<2x3xi32>

      %outputs_4, %control_5 = tf_executor.island wraps "tf.BiasAdd"(%outputs_2, %outputs) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<32xf32>) -> tensor<*xf32>
      %outputs_6, %control_7 = tf_executor.island wraps "tf.Identity"(%outputs_4) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>
      tf_executor.fetch %outputs_6 : tensor<*xf32>
    }
    func.return %0 : tensor<*xf32>
  }

      %outputs_2, %control_3 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<-1> : tensor<i64>} : () -> tensor<i64>
      %outputs_4, %control_5 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<""> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>

    %outputs_6:2, %control_7 = tf_executor.island wraps "tf.While"(%arg0, %arg1) {body = @body, cond = @cond, is_stateless = false, shape_invariant} : (tensor<i32>, tensor<5xf32>) -> (tensor<i32>, tensor<5xf32>) loc("WhileWithOutputShapes")
    tf_executor.fetch %outputs_2#1, %outputs_4#1, %outputs_6#1 : tensor<5xf32>, tensor<5xf32>, tensor<5xf32>
  }