// CHECK:         }
func.func @select_multidimensional(%arg0: tensor<3x2xi1>, %arg1: tensor<3x2xi32>, %arg2: tensor<3x2xi32>) -> tensor<3x2xi32> {
  %0 = "mhlo.select"(%arg0, %arg1, %arg2) : (tensor<3x2xi1>, tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32>
  func.return %0 : tensor<3x2xi32>
}

// CHECK-LABEL:   func @selectv2(
// CHECK-SAME:                   %[[VAL_0:.*]]: tensor<2xi1>,

// CHECK-LABEL: func @bitcast_smaller_output_width
func.func @bitcast_smaller_output_width(%arg0: tensor<2xf32>) -> tensor<2x2xf16> {
  // CHECK:  mhlo.bitcast_convert %arg0 : (tensor<2xf32>) -> tensor<2x2xf16>
  %0 = "tf.Bitcast"(%arg0) : (tensor<2xf32>) -> tensor<2x2xf16>
  func.return %0 : tensor<2x2xf16>
}

// -----

// CHECK-LABEL: squeeze
func.func @squeeze(%arg0: tensor<1x1x10xf32>) -> tensor<1x10xf32> {

func.func @broadcast_to_i16_low_dim(%arg0: tensor<3xi16>, %arg1: tensor<2xi32>) -> tensor<3x3xi16> {
  %0 = "tfl.broadcast_to"(%arg0, %arg1) : (tensor<3xi16>, tensor<2xi32>) -> tensor<3x3xi16>
  return %0 : tensor<3x3xi16>
  // CHECK:  %cst = arith.constant dense<1> : tensor<3x3xi16>
  // CHECK:  %0 = tfl.mul(%arg0, %cst) <{fused_activation_function = "NONE"}> : (tensor<3xi16>, tensor<3x3xi16>) -> tensor<3x3xi16>
  // CHECK:  return %0 : tensor<3x3xi16>