// CHECK:  mhlo.shift_right_logical %[[BROADCAST]], %arg1 : tensor<2x4xui8>
  %0 = "tf.RightShift"(%arg0, %arg1) : (tensor<4xui8>, tensor<2x4xui8>) -> tensor<2x4xui8>
  func.return %0 : tensor<2x4xui8>
}

// CHECK-LABEL: func @and
func.func @and(%arg0: tensor<2xi1>, %arg1: tensor<2xi1>) -> tensor<2xi1> {

    %21 = "tf.Cast"(%20) {Truncate = false} : (tensor<2x2xf32>) -> tensor<2x2xi8>
    %22 = "tf.Identity"(%21) {device = ""} : (tensor<2x2xi8>) -> tensor<2x2xi8>
    %23 = "tf.Identity"(%22) {device = ""} : (tensor<2x2xi8>) -> tensor<2x2xi8>
    %24 = "tf.Cast"(%23) : (tensor<2x2xi8>) -> tensor<2x2xi32>
    %25 = "tf.Sub"(%24, %cst_4) : (tensor<2x2xi32>, tensor<i32>) -> tensor<2x2xi32>

/// 2. realValue is an elements attribute:
/// (realValue: DenseElementsAttr[tensor<2x2xf32>],
///  quantizedElementType: UniformQuantizedType[i8:f32])
///   -> (DenseElementsAttr[tensor<2x2xi8>], outConvertedType: tensor<2x2xi8>)
Attribute quantizeAttr(Attribute realValue,
                       quant::QuantizedType quantizedElementType,
                       Type &outConvertedType);

/// Converts an attribute from a type based on

// CHECK:  return %[[CST]]
}

// CHECK-LABEL: @cast_i1_to_ui8
func.func @cast_i1_to_ui8() -> tensor<2xui8> {
  %cst = arith.constant dense<[false, true]> : tensor<2xi1>
  %0 = "tfl.cast"(%cst) : (tensor<2xi1>) -> tensor<2xui8>
  func.return %0 : tensor<2xui8>

// CHECK: %[[CST:.*]] = arith.constant dense<[0, 1]> : tensor<2xui8>
// CHECK:  return %[[CST]]
}

// CHECK-LABEL: @cast_i8_to_i1

}

func.func @RemoveTrivialSubInt8(%arg0: tensor<2x2xi8>) -> tensor<2x2xi8> {
  %cst = arith.constant dense<0> : tensor<2x2xi8>
  %0 = "tf.Sub"(%arg0, %cst) : (tensor<2x2xi8>, tensor<2x2xi8>) -> tensor<2x2xi8>
  func.return %0 : tensor<2x2xi8>

  // CHECK-LABEL: RemoveTrivialSubInt8
  // CHECK-NEXT: return %arg0 : tensor<2x2xi8>
}

func.func @RemoveTrivialMul(%arg0: tensor<2x2xf32>) -> tensor<2x2xf32> {

  // CHECK: %[[CONVERT_1:.*]] = mhlo.bitcast_convert %[[QUANTIZE]] : (tensor<2x2x!quant.uniform<i8:f32:0, {1.000000e+00:3,2.000000e+00:4}>>) -> tensor<2x2xi8>
  // CHECK: %[[CONVERT_2:.*]] = mhlo.bitcast_convert %[[CONVERT_1]] : (tensor<2x2xi8>) -> tensor<2x2x!quant.uniform<i8:f32:0, {1.000000e+00:3,2.000000e+00:4}>>

  func.return %0 : tensor<!tf_type.string>
}

func.func @uint8() -> tensor<4xui8> {
  // CHECK-LABEL: @uint8
  // CHECK: value = dense<[222, 173, 190, 239]> : tensor<4xui8>
  %0 = "tfl.pseudo_const"() {value = dense<[222, 173, 190, 239]> : tensor<4xui8>} : () -> tensor<4xui8>
  func.return %0 : tensor<4xui8>
}

func.func @int4() -> tensor<5xi4> {
  // CHECK-LABEL: @int4

  func.return %0 : tensor<!tf_type.string>
}

func.func @uint8() -> tensor<4xui8> {
  // CHECK-LABEL: @uint8
  // CHECK: value = dense<[222, 173, 190, 239]> : tensor<4xui8>
  %0 = "tfl.pseudo_const"() {value = dense<[222, 173, 190, 239]> : tensor<4xui8>} : () -> tensor<4xui8>
  func.return %0 : tensor<4xui8>
}

func.func @int4() -> tensor<5xi4> {
  // CHECK-LABEL: @int4

TEST_F(QuantizationReportTest, InitializeWithModuleOp) {
  constexpr absl::string_view kQuantizedDotGeneral = R"mlir(
    func.func @main(%arg0: tensor<1x2xf32>) -> tensor<1x3xf32> {
      %0 = stablehlo.constant() {value = dense<127> : tensor<2x3xi8>} : () -> tensor<2x3x!quant.uniform<i8<-127:127>:f32:1, {1.000000e+0,2.000000e+0,3.000000e+0}>>
      %1 = stablehlo.uniform_quantize %arg0 : (tensor<1x2xf32>) -> tensor<1x2x!quant.uniform<i8:f32, 4.000000e+0>>

    %0 = stablehlo.constant dense<3.000000e+00> : tensor<1x1x1xf32>  // Input inverse scale.
    %1 = stablehlo.constant dense<1> : tensor<1x1x1xi8>  // Input zero point.
    %2 = stablehlo.constant dense<5> : tensor<2x3xi8>  // Quantized filter.
    %3 = stablehlo.constant dense<4> : tensor<1x1x3xi32>  // Precalculated q2 * z1.
    %4 = stablehlo.constant dense<3.000000e+03> : tensor<1x1x3xf32>  // Merged scale: s1 * s2.