// CHECK:           %[[VAL_14:.*]] = "tf.Abs"(%[[VAL_1]]) : (tensor<2x3xi32>) -> tensor<2x3xi32>
// CHECK:           %[[VAL_15:.*]] = "tf.Div"(%[[VAL_13]], %[[VAL_14]]) : (tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>
// CHECK:           %[[VAL_16:.*]] = "tf.Select"(%[[VAL_6]], %[[VAL_7]], %[[VAL_15]]) : (tensor<2x3xi1>, tensor<2x3xi32>, tensor<2x3xi32>) -> tensor<2x3xi32>

  // CHECK-NEXT: %[[SELECT:.*]] = mhlo.select %arg0, %arg1, %arg2 : tensor<?x?x8xi1>, tensor<?x?x8xi32>
  // CHECK-NEXT: shape.assuming_yield %[[SELECT]] : tensor<?x?x8xi32>
  %0 = "tf.Select"(%arg0, %arg1, %arg2) : (tensor<?x?x8xi1>, tensor<?x?x8xi32>, tensor<?x?x8xi32>) -> tensor<?x?x8xi32>
  func.return %0: tensor<?x?x8xi32>
}

// -----

  %0 = "tfl.broadcast_to"(%arg0, %arg1) : (tensor<3xi32>, tensor<2xi32>) -> tensor<3x3xi32>
  return %0 : tensor<3x3xi32>
  // CHECK:  %cst = arith.constant dense<1> : tensor<3x3xi32>
  // CHECK:  %0 = tfl.mul(%arg0, %cst) <{fused_activation_function = "NONE"}> : (tensor<3xi32>, tensor<3x3xi32>) -> tensor<3x3xi32>
  // CHECK:  return %0 : tensor<3x3xi32>
}

  %19 = "tf.StringLength"(%arg0) {device = "", unit = "BYTE"} : (tensor<1x!tf_type.string>) -> tensor<1xi32>
  %20 = "tf.ExpandDims"(%19, %7) {device = ""} : (tensor<1xi32>, tensor<i32>) -> tensor<1x1xi32>
  %21 = "tf.Cast"(%20) {Truncate = false, device = ""} : (tensor<1x1xi32>) -> tensor<1x1xi64>
  %22 = "tf.Reshape"(%21, %12) {device = ""} : (tensor<1x1xi64>, tensor<1xi64>) -> tensor<1xi64>