%0 = "tf.Const"() {device = "/device:CPU:0", value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %1 = "tf.AddV2"(%arg0, %0) {device = "/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    %2 = "tf.Div"(%arg1, %0) {device = "/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
    func.return %1, %2 : tensor<i32>, tensor<i32>
  }

  %b0 = "tf.Sub"(%b, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %b1 = "tf.Sub"(%b0, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %b2 = "tf.Sub"(%b1, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %b3 = "tf.Sub"(%b2, %b) : (tensor<i32>, tensor<i32>) -> tensor<i32>

  %c = "tf.AddV2"(%a3, %b3) : (tensor<i32>, tensor<i32>) -> tensor<i32>

  func.return %c : tensor<i32>

      %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>
      tf_executor.fetch %outputs_8 : tensor<i32>
    }
    func.return %0 : tensor<i32>
  }
}

  func.func @convert_cluster_func(%arg0: tensor<i32>) -> tensor<i32> {
    // CHECK: "tf.XlaLaunch"(%arg0) <{function = @func, operandSegmentSizes = array<i32: 0, 1, 0>}> : (tensor<i32>) -> tensor<i32>
    %0 = "tf_device.cluster_func"(%arg0) {func = @func} : (tensor<i32>) -> tensor<i32>
    func.return %0 : tensor<i32>
  }

  func.func @func(%arg0: tensor<i32>) -> tensor<i32> {
    func.return %arg0 : tensor<i32>
  }
}

// -----

        tf_executor.yield %1, %2, %3, %4 : tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>
      }
      tf_executor.fetch %outputs#0, %outputs#1, %outputs#2, %outputs#3 : tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>

    }
    func.return %0#0 : tensor<i32>
  }
  func.func @while_body_with_cluster_attr(%arg0: tensor<i32>) -> tensor<i32> {

  %1 = "tf.Reciprocal"(%0) : (tensor<i32>) -> tensor<i32>
  %2 = "tf.Reciprocal"(%1) : (tensor<i32>) -> tensor<i32>
  // CHECK: return [[RECIPROCAL]]
  func.return %2: tensor<i32>
}

// CHECK-LABEL: func @testSingleInvert
// CHECK-SAME:  ([[ARG0:%.+]]: tensor<i32>)
func.func @testSingleInvert(%arg0: tensor<i32>) -> tensor<i32> {
  // CHECK: [[INVERT:%.+]] = "tf.Invert"([[ARG0]])
  %0 = "tf.Invert"(%arg0) : (tensor<i32>) -> tensor<i32>

  %1 = "tf.ReadVariableOp"(%arg) {device = "/device:CPU:0", dtype = i32} : (tensor<!tf_type.resource<tensor<i32>>>) -> tensor<i32>
  %2 = "tf.Add"(%1, %0) {device = "/device:CPU:0"} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  "tf.AssignVariableOp"(%arg, %2) {device = "/device:CPU:0"} : (tensor<!tf_type.resource<tensor<i32>>>, tensor<i32>) -> ()
  func.return %arg : tensor<!tf_type.resource<tensor<i32>>>
}

func.func private @"random/while_cond/TfMlrtAsyncWhilePredicate"(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<i32> {

  %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
  return %0: tensor<i32>
}

// CHECK-LABEL: func.func private @"random/while_body/TfMlrtAsyncWhileBody"(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<i32> {

  "tf.AssignVariableOp"(%arg1, %0#1) : (tensor<*x!tf_type.resource<tensor<i32>>>, tensor<i32>) -> ()
  func.return
}

// CHECK-LABEL: func @multiple_write_func
// CHECK-SAME: ({{%.*}}: tensor<i32>) -> (tensor<i32>, tensor<i32>)
func.func @multiple_write_func(%arg0: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  func.return %arg0, %arg0 : tensor<i32>, tensor<i32>
}

    "tfl.yield"(%1#0, %1#1) : (tensor<*xi32>, tensor<*xf32>) -> ()
  }) : (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>) loc("WhileOp")
  // CHECK: (tensor<i32>, tensor<1xf32>, tensor<i32>) ->
  // CHECK-SAME: (tensor<i32>, tensor<1xf32>, tensor<i32>)
  func.return %0#1 : tensor<1xf32>
}

func.func private @WhileOp_cond(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>, %arg2: tensor<i32>) -> tensor<i1> {