%7 = "tf.FloorDiv"(%arg1, %5) {device = ""} : (tensor<1x1x2x1xi32>, tensor<i32>) -> tensor<1x1x2x1xi32>
  %8 = "tf.FloorMod"(%7, %4) {device = ""} : (tensor<1x1x2x1xi32>, tensor<i32>) -> tensor<1x1x2x1xi32>
  %9 = "tf.FloorDiv"(%arg1, %4) {device = ""} : (tensor<1x1x2x1xi32>, tensor<i32>) -> tensor<1x1x2x1xi32>

func.func @add_with_i32_five_dim_broadcasting(tensor<1x1x1x1x1xi32>, tensor<1xi32>) -> tensor<1x1x1x1x1xi32> {
^bb0(%arg0: tensor<1x1x1x1x1xi32>, %arg1: tensor<1xi32>):
  // CHECK: tfl.add(%arg0, %arg1) <{fused_activation_function = "RELU6"}>
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1x1x1x1x1xi32>, tensor<1xi32>) -> tensor<1x1x1x1x1xi32>
  func.return %0#0 : tensor<1x1x1x1x1xi32>
}

// -----

func.func @test5DAddWithImplicitBroadcast(%arg0: tensor<1x1x1x3x1xi32>, %arg1 : tensor<1x1x1x1x4xi32>) -> tensor<1x1x1x3x4xi32> {
  %0 = "tf.Add"(%arg0, %arg1): (tensor<1x1x1x3x1xi32>, tensor<1x1x1x1x4xi32>) -> tensor<1x1x1x3x4xi32>
  func.return %0 : tensor<1x1x1x3x4xi32>
// CHECK-LABEL: test5DAddWithImplicitBroadcast
// CHECK: %0 = tfl.add(%arg0, %arg1) <{fused_activation_function = "NONE"}> : (tensor<1x1x1x3x1xi32>, tensor<1x1x1x1x4xi32>) -> tensor<1x1x1x3x4xi32>