<< ", FallbackEnabled: " << num_passes_fallback_enabled
                         << ", Total: " << registry_->passes().size();
  }

  GraphDebugInfo debug_info;
  mlir::DialectRegistry registry;
  RegisterDialects(registry);
  mlir::MLIRContext context(registry);
  GraphImportConfig import_config;
  import_config.graph_as_function = true;
  import_config.control_outputs = *control_ret_node_names;

};

SymbolicGradientBuilder::SymbolicGradientBuilder(
    const Scope& scope, const ops::GradOpRegistry* registry,
    const std::vector<Output>& outputs, const std::vector<Output>& inputs,
    const std::vector<Output>& grad_inputs, std::vector<Output>* grad_outputs)
    : scope_(scope),
      registry_(registry),
      outputs_(outputs),
      inputs_(inputs),
      grad_inputs_(grad_inputs),

Status GradientRegistry::Register(
    const string& op_name, GradientFunctionFactory gradient_function_factory) {
  auto iter = registry_.find(op_name);
  if (iter != registry_.end()) {
    const string error_msg = "Gradient already exists for op: " + op_name + ".";
    return errors::AlreadyExists(error_msg);
  }
  registry_.insert({op_name, gradient_function_factory});
  return absl::OkStatus();
}
Status GradientRegistry::Lookup(

          XlaCallModuleDeserializationPass> {
 public:
  void getDependentDialects(mlir::DialectRegistry &registry) const override {
    XlaCallModuleDeserializationPassBase::getDependentDialects(registry);
    mlir::func::registerAllExtensions(registry);
  }

  void runOnOperation() override {
    ModuleOp module = getOperation();
    SymbolTableCollection symbol_tables;

    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,
                                          const std::string& content) {

  std::iota(input_mapping->begin(), input_mapping->end(), 0);
}

static void RegisterDialects(mlir::DialectRegistry& registry) {
  mlir::RegisterAllTensorFlowDialects(registry);
  mlir::mhlo::registerAllMhloDialects(registry);
  mlir::stablehlo::registerAllDialects(registry);
}

// Checks if functions can be inlined after TF -> HLO legalization. Currently

    // This is a brief description of the pass.
    return "Import quantization stats to the model";
  }

  void runOnOperation() override;

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

  // Parses the serialized quant stats protobuf and initialize the internal

    }
    return success();
  }
};

class LiftTfliteFlexOpsPass
    : public impl::LiftTfliteFlexOpsPassBase<LiftTfliteFlexOpsPass> {
  void getDependentDialects(DialectRegistry& registry) const override {
    registry.insert<TF::TensorFlowDialect>();
  }

 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(LiftTfliteFlexOpsPass)

  void runOnOperation() override {

  StringRef getDescription() const final {
    return "Unfuses MHLO batch norm inference op into arithmetic ops";
  }
  void getDependentDialects(::mlir::DialectRegistry &registry) const override {
    // TODO(b/299514833): Remove TensorFlowDialect usage.
    registry.insert<shape::ShapeDialect, mlir::TF::TensorFlowDialect>();
  }

  void runOnOperation() override {
    RewritePatternSet patterns(&getContext());

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Quantize weights used by quantizable ops.";
  }

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

 private:
  void runOnOperation() override;

  bool test_mode_;
  tensorflow::quantization::QuantizationOptions quant_options_;