func.func @valid_unranked_inputs_on_reshape(%arg0: tensor<3x4xi32>, %arg1: tensor<*xi32>) -> tensor<3x4xi32> {
  // CHECK: "tfl.reshape"(%arg0, %arg1)
  %0 = "tfl.reshape"(%arg0, %arg1) : (tensor<3x4xi32>, tensor<*xi32>) -> tensor<3x4xi32>
  func.return %0 : tensor<3x4xi32>
}

// -----

// CHECK-LABEL: valid_one_dynamic_dim_on_reshape
func.func @valid_one_dynamic_dim_on_reshape(%arg0: tensor<3x4xi32>) -> tensor<1x3x4xi32> {

func.func @testBitcast(%arg0: tensor<3x4xui16>) -> tensor<3x4x!tf_type.quint16> {
  %0 = "tf.Bitcast"(%arg0) : (tensor<3x4xui16>) -> tensor<3x4x!tf_type.quint16>
  func.return %0 : tensor<3x4x!tf_type.quint16>
}

// -----

// CHECK-LABEL: func @testBitcast_v2
func.func @testBitcast_v2(%arg0: tensor<3x2xi16>) -> tensor<3xi32> {
  %0 = "tf.Bitcast"(%arg0) : (tensor<3x2xi16>) -> tensor<3xi32>
  func.return %0 : tensor<3xi32>
}

}

func.func @concat_v2_with_bool_type(%arg0: tensor<?x1xi1>, %arg1: tensor<?x1xi1>) -> tensor<?x2xi1> {
  %0 = "tf.Const"() { value = dense<-1> : tensor<i32> } : () -> tensor<i32>
  %1 = "tf.ConcatV2"(%arg0, %arg1, %0) : (tensor<?x1xi1>, tensor<?x1xi1>, tensor<i32>) -> tensor<?x2xi1>
  func.return %1 : tensor<?x2xi1>

// CHECK-LABEL: concat_v2_with_bool_type

func.func @select(
    %arg0: tensor<1x3xi1>,
    %arg1: tensor<1x3x!quant.uniform<i8:f32, 2.000000e+00:-1>>,
    %arg2: tensor<1x3x!quant.uniform<i8:f32, 2.000000e+00:-1>>
  ) -> tensor<1x3x!quant.uniform<i8:f32, 2.000000e+00:-1>> {
  %0 = "stablehlo.select"(%arg0, %arg1, %arg2) : (
    tensor<1x3xi1>,
    tensor<1x3x!quant.uniform<i8:f32, 2.000000e+00:-1>>,