func.func @ReorderAddWithConstant(%arg0: tensor<2x2xf32>) -> tensor<2x2xf32> {
  %cst = arith.constant dense<1.0> : tensor<2x2xf32>
  %cst_1 = arith.constant dense<2.0> : tensor<2x2xf32>
  %0 = "tfl.add"(%arg0, %cst) {fused_activation_function = "NONE"} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>
  %1 = "tfl.add"(%0, %cst_1) {fused_activation_function = "NONE"} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32>

// CHECK:             mhlo.return %[[VAL_5]] : tensor<f32>
// CHECK:           }) : (tensor<20x6xf32>, tensor<4xi32>, tensor<4x6xf32>) -> tensor<20x6xf32>
// CHECK:           return %[[VAL_3]] : tensor<20x6xf32>
// CHECK:         }
func.func @convert_scatter_update(%arg0: tensor<20x6xf32>, %arg1: tensor<4xi32>, %arg2: tensor<4x6xf32>) -> tensor<20x6xf32> {
  %0 = "mhlo.scatter"(%arg0, %arg1, %arg2) ({
  ^bb0(%arg3: tensor<f32>, %arg4: tensor<f32>):

  // CHECK: return %[[RESULT]]
  func.return %0: tensor<10x2xf32>
}

// -----

func.func @select_first(%arg0: tensor<10x2xf32>, %arg1: tensor<10x2xf32>) -> tensor<10x2xf32> {
  func.return %arg0: tensor<10x2xf32>
}

// CHECK-LABEL: testMultiInputLegacyCallOp
func.func @testMultiInputLegacyCallOp(%arg0: tensor<10x2xf32>, %arg1: tensor<10x2xf32>) -> tensor<10x2xf32> {