skip_resize_ = pass.skip_resize_;
    skip_partitioned_calls_ = pass.skip_partitioned_calls_;
  }

 private:
  void runOnOperation() override;

  void getDependentDialects(DialectRegistry &registry) const override {
    mlir::mhlo::registerAllMhloDialects(registry);
    mlir::stablehlo::registerAllDialects(registry);
    registry.insert<mlir::func::FuncDialect, mlir::arith::ArithDialect>();

    // This is a brief description of the pass.
    return "Replace quantization candidates with composite functions into the "
           "module for post-training dynamic range case";
  }

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect>();
  }

  void runOnOperation() override;

 private:
  Option<OpSet> target_opset_{

      MLIRContext* context) const = 0;

  // Returns TypeId for the provided hardware.
  // Usually should be something like mlir::TypeID::get<MyType>()
  virtual mlir::TypeID GetTypeId() const = 0;

  virtual void GetDependentDialects(mlir::DialectRegistry& registry) const {}

 protected:
  // All registered hardware ops.
  std::vector<std::unique_ptr<TargetHardwareOperation>> hardware_ops_;
};

#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_savedmodel_passes.h.inc"
class LowerGlobalsToMlProgram
    : public impl::LowerGlobalsToMlProgramPassBase<LowerGlobalsToMlProgram> {
 public:
  void getDependentDialects(DialectRegistry &registry) const override {
    registry.insert<mlir::tf_saved_model::TensorFlowSavedModelDialect,
                    ml_program::MLProgramDialect>();
  }

  void runOnOperation() override {

  explicit LegalizeTFToQuant() = default;
  LegalizeTFToQuant(const LegalizeTFToQuant &) {}

  /// Performs the lowering to Quant ops dialect.
  void runOnOperation() override;

  void getDependentDialects(DialectRegistry &registry) const override {
    registry.insert<quant::QuantizationDialect,
                    quantfork::QuantizationForkDialect>();
  }

  StringRef getArgument() const final {

  }

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Insert quantized functions into the module";
  }

  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, func::FuncDialect>();
  }

 private:
  void runOnOperation() override;

// belong to 'tf' or '_tf' dialect. The output is in '_tf' dialect.
class GraphOptPass
    : public mlir::PassWrapper<GraphOptPass,
                               mlir::OperationPass<mlir::ModuleOp>> {
  void getDependentDialects(mlir::DialectRegistry& registry) const override {
    mlir::RegisterAllTensorFlowDialects(registry);
  }

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(GraphOptPass)

// Applies prepare quantization on the model in TF dialect for dynamic range
// quantization case.
class PrepareQuantizeDRQPass
    : public PassWrapper<PrepareQuantizeDRQPass, OperationPass<ModuleOp>> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect, ::mlir::quant::QuantizationDialect,
                    ::mlir::quantfork::QuantizationForkDialect>();
  }

 public:

  StringRef getArgument() const final { return "constant-fold-broadcast-pass"; }
  StringRef getDescription() const final {
    return "Constant folds BroadcastInDimOp before binary elementwise ops";
  }
  void getDependentDialects(::mlir::DialectRegistry &registry) const override {}

  void runOnOperation() override {
    RewritePatternSet patterns(&getContext());
    patterns.add<FoldBroadcastInDimBeforeMulOp>(&getContext());

  StringRef getDescription() const final {
    return "This pass will legalize TFLite custom Ops to StableHLO ops.";
  }

 private:
  void runOnOperation() override;

  void getDependentDialects(DialectRegistry& registry) const override {
    mlir::stablehlo::registerAllDialects(registry);
  }
  inline TFL::ConstBytesAttr CustomOption(OpBuilder* builder,