const tsl::protobuf::Message& x) {
  return ::testing::MakePolymorphicMatcher(ProtoStringMatcher(x));
}

void FillPresetQuantizationOptionsTestHelper(
    const PresetQuantizationMethod::PresetMethod preset_quantization_options,
    const QuantizationComponentSpec expected_activation_component,
    const QuantizationComponentSpec expected_weight_component,
    const QuantizationComponentSpec expected_bias_component) {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_dialect.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir::quant {
namespace {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;

class EmptyPatternRewriter : public mlir::PatternRewriter {
 public:
  explicit EmptyPatternRewriter(const OpBuilder& op_builder)
      : mlir::PatternRewriter(op_builder) {}

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace quant {
namespace {

using QuantMethod =
    ::tensorflow::quantization::QuantizationMethod::PresetMethod;
using ::tensorflow::quantization::OpSet;

class LiftQuantizableSpotsAsFunctionsDRQPass
    : public PassWrapper<LiftQuantizableSpotsAsFunctionsDRQPass,
                         OperationPass<ModuleOp>> {
 public:

#include "tensorflow/compiler/mlir/tensorflow/utils/error_util.h"

namespace mlir {
namespace quant {
namespace {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;
using ::tensorflow::quantization::OpSet;

class InsertQuantizedFunctionsPass
    : public PassWrapper<InsertQuantizedFunctionsPass,
                         OperationPass<ModuleOp>> {
 public:

// The preprocess-op Pass.
//
namespace mlir {
namespace quant {

namespace {

using QuantMethod =
    ::tensorflow::quantization::QuantizationMethod::PresetMethod;
using QuantizationUnit = std::pair<Operation*, int>;
using QuantizationUnits = llvm::SetVector<QuantizationUnit>;
using ::tensorflow::quantization::OpSet;

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"
#include "tensorflow/core/util/quantization/uniform_quant_ops_attr.pb.h"

namespace mlir::quant {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;

enum class OpType {
  kDynamicRangeOp,  // Dynamic Range kernels only have rhs attr.
  kUnaryOp,         // Unary ops have one min/max attr.
  kBinaryOp,        // Binary ops have lhs/rhs attr.

// The prepare-quantize Pass.
//
namespace mlir {
namespace quant {

namespace {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;

// Applies prepare quantization on the model in TF dialect. This pass runs
// before the quantization pass and propagate the quantization parameters

#include "tensorflow/core/ir/importexport/convert_tensor.h"

namespace mlir {
namespace quant {
namespace {

using QuantMethod = tensorflow::quantization::QuantizationMethod::PresetMethod;
using ::tensorflow::quantization::OpSet;

constexpr absl::string_view kQuantizeCompositeFunctionsStepName =
    "_quantize_composite_functions";
constexpr StringRef kQuantizeFuncName = "quantize_i8";