}

TEST_F(ConvertTfQuantToMhloIntTest, UniformRequantizeToValidGraph) {
  constexpr absl::string_view kProgram = R"mlir(
func.func @main(%input: tensor<10xi8>) -> tensor<10xi8> {
  %input_scale = "tf.Const"() { value = dense<0.2235> : tensor<f32> } : () -> tensor<f32>
  %input_zp = "tf.Const"() { value = dense<-2> : tensor<i32> } : () -> tensor<i32>

          )
      )
      module_str = self._extract_first_xla_call_module_op(
          self._output_saved_model_path
      )
      self.assertTrue(
          re.search('stablehlo.dot_general.*xi8>.*xi8>.*xi32>', module_str)
      )

    # Run quantization the first time, calibration is expected to be skipped.
    output_saved_model_path_2 = self.create_tempdir('output2').full_path

  if (!quantDenseAttr) {
    return nullptr;
  }

  // Cast from an expressed-type-based type to storage-type-based type,
  // preserving the sparse shape (i.e. tensor<4xf32> -> tensor<4xi8>).
  ShapedType newSparseType = mlir::dyn_cast_or_null<ShapedType>(
      quantizedElementType.castExpressedToStorageType(
          realSparseAttr.getType()));
  if (!newSparseType) {
    return nullptr;
  }

// CHECK-LABEL: fused_conv2d
func.func @fused_conv2d(%input: tensor<1x300x300x40xi8>,
                        %filter: tensor<3x3x40x40xi8>,
                        %bias: tensor<40xf32>,
                        %act: tensor<0xi8>) -> tensor<1x300x300x40xi8> {

  // CHECK:       %[[v0:.*]] = mhlo.constant dense<1.000000e+00> : tensor<f32>
  // CHECK-NEXT:  %[[v1:.*]] = mhlo.constant dense<2.000000e+00> : tensor<f32>

// CHECK: %[[maxpool:.*]] = "tf.MaxPool"(%[[conv_quant]]) <{data_format = "NHWC", ksize = [1, 2, 2, 1], padding = "VALID", strides = [1, 1, 1, 1]}> : (tensor<*xi8>) -> tensor<*xi8>
// CHECK: %[[dequantize:.*]] = "tf.PartitionedCall"(%[[maxpool]]
// CHECK-SAME: f = @dequantize_i8
// CHECK: return %[[dequantize]]

// Test invalid tf.ToBool
func.func @testInvalidToBool(%arg0: tensor<i32>) -> tensor<1xi1> {
  // expected-error @+2 {{'tf.ToBool' op failed to infer returned types}}
  // expected-error @+1 {{op inferred type(s) 'tensor<i1>' are incompatible with return type(s) of operation 'tensor<1xi1>'}}
  %0 = "tf.ToBool"(%arg0) : (tensor<i32>) -> tensor<1xi1>
  func.return %0 : tensor<1xi1>
}

// -----

  // CHECK: tf.Conv2DBackpropInput
}

func.func @assert_remove(%arg0: tensor<1xi32>, %arg1: tensor<1xi32>) -> tensor<1xi1> {
  %0 = "tf.LessEqual"(%arg0, %arg1) : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi1>
  "tf.Assert"(%0, %arg1) {summarize = 3} : (tensor<1xi1>, tensor<1xi32>) -> ()
  func.return %0 : tensor<1xi1>
  // CHECK-LABEL: assert_remove
  // CHECK: tfl.less_equal
  // CHECK-NOT: Assert
  // CHECK: return
}

}

// -----

// CHECK-LABEL: func @bitcast_smaller_input_width
func.func @bitcast_smaller_input_width(%arg0: tensor<8xi8>) -> tensor<i64> {
  // CHECK:  mhlo.bitcast_convert %arg0 : (tensor<8xi8>) -> tensor<i64>
  %0 = "tf.Bitcast"(%arg0) : (tensor<8xi8>) -> tensor<i64>
  func.return %0 : tensor<i64>
}

// -----

// CHECK-LABEL: func @bitcast_smaller_output_width

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