mlir::tf_executor::TensorFlowExecutorDialect,
                  mlir::vhlo::VhloDialect>();
  mlir::mhlo::registerAllMhloDialects(registry);
  mlir::func::registerAllExtensions(registry);
  return failed(
      mlir::MlirOptMain(argc, argv, "StableHLO quant Pass Driver\n", registry));

         "or compilation failure from the MLIR bridge (full fallback mode).";

  mlir::DialectRegistry registry;
  mlir::RegisterAllTensorFlowDialects(registry);
  mlir::mhlo::registerAllMhloDialects(registry);
  mlir::stablehlo::registerAllDialects(registry);
  mlir::MLIRContext context(registry);
  mlir::OwningOpRef<mlir::ModuleOp> mlir_module;
  TF_RETURN_IF_ERROR(

  }

 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>();
    registry.insert<shape::ShapeDialect>();
  }

 public:
  StringRef getArgument() const final { return "tf-mhlo"; }

  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 {
    // This is the argument used to refer to the pass in

            tflite::RegisterCustomOpdefs(custom_opdefs_txt_raw.ptr()));
      },
      py::arg("custom_opdefs_txt_raw"),
      R"pbdoc(
      Registers the given custom opdefs to the TensorFlow global op registry.
    )pbdoc");
  m.def(
      "RetrieveCollectedErrors",
      []() {
        std::vector<std::string> collected_errors =
            tflite::RetrieveCollectedErrors();

                   "allowlist) as select Tensorflow ops"),
    llvm::cl::init(false));

// The following approach allows injecting opdefs in addition
// to those that are already part of the global TF registry  to be linked in
// prior to importing the graph. The primary goal is for support of custom ops.
// This is not intended to be a general solution for custom ops for the future

void Register(const std::string& op_name, OpRegistry* registry) {
  registry->Register([op_name](OpRegistrationData* op_reg_data) -> Status {
    op_reg_data->op_def.set_name(op_name);
    return absl::OkStatus();
  });
}

}  // namespace

TEST(TfTextUtilsTest, TestTfTextRegistered) {
  std::unique_ptr<OpRegistry> registry(new OpRegistry);
  Register("WhitespaceTokenizeWithOffsets", registry.get());

    MlirToFlatBufferFileTranslateFunction, [](DialectRegistry& registry) {
      registry.insert<quant::QuantizationDialect,
                      quantfork::QuantizationForkDialect>();
      mlir::RegisterAllTensorFlowDialects(registry);
      registry.insert<TFL::TensorFlowLiteDialect>();
      registry.insert<arith::ArithDialect>();
      registry.insert<func::FuncDialect>();
      registry.insert<mlir::vhlo::VhloDialect>();

PYBIND11_MODULE(tfr_wrapper, m) {
  m.def("verify", [](std::string input) {
    mlir::DialectRegistry registry;
    registry.insert<mlir::arith::ArithDialect, mlir::scf::SCFDialect,
                    mlir::TF::TensorFlowDialect, mlir::func::FuncDialect,
                    mlir::shape::ShapeDialect, mlir::TFR::TFRDialect>();
    mlir::MLIRContext ctx(registry);
    ctx.loadAllAvailableDialects();

    llvm::SourceMgr source_mgr = llvm::SourceMgr();

  mlir::DialectRegistry registry;
  mlir::registerAllDialects(registry);
  mlir::RegisterAllTensorFlowDialects(registry);

  mlir::registerAllPasses();
  mlir::registerTensorFlowPasses();

  EXPECT_TRUE(mlir::MlirOptMain(output_stream->os(), std::move(input_file),
                                registry,
                                mlir::MlirOptMainConfig{}