%0 = arith.constant dense<-1> : tensor<1xi32>
  %1 = "tfl.reduce_max"(%arg0, %0) {keep_dims = true} : (tensor<10x10xf32>, tensor<1xi32>) -> tensor<10x1xf32>
  %2 = tfl.sub(%arg0, %1) {fused_activation_function = "NONE"} : (tensor<10x10xf32>, tensor<10x1xf32>) -> tensor<10x10xf32>
  %3 = "tfl.exp"(%2) : (tensor<10x10xf32>) -> tensor<10x10xf32>

  // CHECK-DAG: %[[IOTA0:.*]] = "mhlo.iota"() <{iota_dimension = 0 : i64}> : () -> tensor<12x12xi32>
  // CHECK-DAG: %[[IOTA1:.*]] = "mhlo.iota"() <{iota_dimension = 1 : i64}> : () -> tensor<12x12xi32>
  // CHECK-DAG: %[[COMP:.*]] = mhlo.compare EQ, %[[IOTA0]], %[[IOTA1]], NOTYPE : (tensor<12x12xi32>, tensor<12x12xi32>) -> tensor<12x12xi1>
  // CHECK-DAG: %[[ZERO:.*]] = mhlo.constant dense<0.000000e+00> : tensor<f32>

  %0 = "mhlo.broadcast_in_dim"(%arg1) <{broadcast_dimensions = dense<[0, 1]> : tensor<2xi64>}> : (tensor<1x1xi32>) -> tensor<1x100xi32>
  %1 = "mhlo.select"(%arg0, %0, %arg2) : (tensor<i1>, tensor<1x100xi32>, tensor<1x100xi32>) -> tensor<1x100xi32>
  func.return %1 : tensor<1x100xi32>
}

// CHECK-LABEL:   func @selectv2_broadcasted_condition(

  %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>