%3:3 = tf_executor.Merge %2#0, %0#0 : tensor<*x!tf_type.int32ref> {device = "", N = 2, T = "tfdtype$DT_INT32"} loc("while/Merge")
    %4:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("while/Less/y")

    %3:3 = tf_executor.Merge %2#0, %0#0 : tensor<*xi32> {device = "", N = 2, T = "tfdtype$DT_INT32"} loc("while/Merge")
    %4:2 = tf_executor.island(%3#2) wraps "tf.Const"() {device = "", dtype = "tfdtype$DT_INT32", value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("while/Less/y")

    %0:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> (tensor<i32>) loc("foo")
    // CHECK: name: "foo{{_.*_1}}"
    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<1> : tensor<i32>} : () -> (tensor<i32>) loc("foo")
    // CHECK: name: "foo1"

    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> tensor<i32>
    %2:2 = tf_executor.Enter %1#0 frame "while/while_context" : (tensor<i32>) -> (tensor<*xi32>, !tf_executor.control) {T = "tfdtype$DT_INT32"}
    %3:3 = tf_executor.Merge %2#0, %0#0 : tensor<*xi32> {N = 2 : i64, T = "tfdtype$DT_INT32"}

    %0:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> (tensor<i32>) loc("^foo")
    // CHECK: name: "fo.o"
    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<1> : tensor<i32>} : () -> (tensor<i32>) loc("fo{o")
    // CHECK: name: "foo"

    // The following node would be renamed to bar2
    %3:2 = tf_executor.island wraps "tf.Identity"(%2) {device = "", dtype = "tfdtype$DT_INT32"} : (tensor<10xi32>) -> tensor<10xi32> loc ("bar")

    %4:2 = tf_executor.island wraps "tf.Mul"(%2#1, %2#0) {T = "tfdtype$DT_INT32", device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32> loc("Square")
    %5:3 = tf_executor.Merge %3#0, %4#0 : tensor<i32> {device = "", N = 2, T = "tfdtype$DT_INT32"} loc("Merge")
    tf_executor.fetch
  }
  func.return

func.func @replicate_arg_shape(%arg0: tensor<*xf32>, %arg1: tensor<*xf32>) {
  %0:4 = tf_device.replicate([%arg0, %arg1] as %ri: tensor<*xf32>) {n = 2: i32} {
    %1 = "tf.Shape"(%ri) {device = "", T = "tfdtype$DT_FLOAT", out_type = "tfdtype$DT_INT32"} : (tensor<*xf32>) -> tensor<?xi32>
    %2 = "tf.opA"(%1, %ri) : (tensor<?xi32>, tensor<*xf32>) -> tensor<*xi32>
    tf_device.return %1, %2 : tensor<?xi32>, tensor<*xi32>
  }
  func.return
}

    %4:2 = tf_executor.island wraps "tf.Mul"(%2#1, %2#1) {T = "tfdtype$DT_INT32"} : (tensor<i32>, tensor<i32>) -> tensor<i32> loc("Multiplication")
    %5:3 = tf_executor.Merge %3#0, %4#0 : tensor<i32> {device = "", N = 2, T = "tfdtype$DT_INT32"} loc("Merge")
    tf_executor.fetch
  }
  func.return
}

// CHECK: dim
// CHECK: size: 10

func.func @main() {
  tf_executor.graph {
    %0:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<10xi32>} : () -> tensor<10xi32>
    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> tensor<i32>