}

func.func @consecutive_add_sub(%arg0: tensor<i32>) -> (tensor<i32>) {
  %cst = "tf.Const"() {value = dense<-18> : tensor<i32>} : () -> tensor<i32>
  %cst_1 = "tf.Const"() {value = dense<-12> : tensor<i32>} : () -> tensor<i32>
  %0 = "tf.AddV2"(%arg0, %cst) {T = i32, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %1 = "tf.Sub"(%0, %cst_1) {T = i32, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  return %1 : tensor<i32>

  %1 = "tf.PartitionedCall"(%arg0) {config = "", config_proto = "", executor_type = "", f = @callee1} : (tensor<i32>) -> tensor<i32>
  func.return %1 : tensor<i32>
}

// CHECK-LABEL: func @callee1
// CHECK-SAME: ([[ARG0:%.*]]: tensor<i32>)
func.func @callee1(%arg0: tensor<i32>) -> tensor<i32> {
  // CHECK-NOT:  "tf.Identity"
  // CHECK:      return [[ARG0]]
  %0 = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>

// CHECK: "tf.opA"
// CHECK-NOT: island
// CHECK: name = "A"
// CHECK-NOT: island
// CHECK: name = "C"
// CHECK-NOT: island
// CHECK: name = "E"
// CHECK: island {{.*}}name = "B"
// CHECK: island {{.*}}name = "D"

    tf_executor.fetch %1#0, %2#0, %3#0, %4#0, %5#0, %6#0 : tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>, tensor<i32>
  }
  func.return %0#0 : tensor<i32>
}

    %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>

  "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>
}