%1 = "tfl.neg"(%arg0) : (tensor<2x3xf32>) -> tensor<2x3xf32>
  %2 = "tfl.relu"(%1) : (tensor<2x3xf32>) -> tensor<2x3xf32>
  %3 = "tfl.mul"(%alpha, %2) {fused_activation_function = "NONE"} : (tensor<f32>, tensor<2x3xf32>) -> tensor<2x3xf32>
  %4 = "tfl.add"(%0, %3) {fused_activation_function = "NONE"} : (tensor<2x3xf32>, tensor<2x3xf32>) -> tensor<2x3xf32>
  func.return %4 : tensor<2x3xf32>

func.func @concat_v2(%arg0: tensor<3x3xf32>, %arg1: tensor<3x3xf32>) -> tensor<6x3xf32> {
  // CHECK: "mhlo.concatenate"({{.*}}) <{dimension = 0 : i64}> : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<6x3xf32>
  %axis = "tf.Const"() { value = dense<0> : tensor<i64> } : () -> tensor<i64>
  %1 = "tf.ConcatV2"(%arg0, %arg1, %axis) : (tensor<3x3xf32>, tensor<3x3xf32>, tensor<i64>) -> tensor<6x3xf32>
  func.return %1 : tensor<6x3xf32>
}

func.func @concat_v2(%arg0: tensor<3x3xf32>, %arg1: tensor<3x3xf32>) -> tensor<6x3xf32> {
  %2 = "mhlo.concatenate"(%arg0, %arg1) <{dimension = 0 : i64}> : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<6x3xf32>
  func.return %2 : tensor<6x3xf32>
}

// CHECK-LABEL:   func @concat_v2_1d_axis(
// CHECK-SAME:                            %[[VAL_0:.*]]: tensor<3x3xf32>,
// CHECK-SAME:                            %[[VAL_1:.*]]: tensor<3x3xf32>) -> tensor<3x6xf32> {