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;

  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

    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_;

            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();

  StringRef getDescription() const final {
    // This is a brief description of the pass.
    return "Apply converting Tensorflow Xla ops to non-xla ops.";
  }

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

  void runOnOperation() override;
};

// Generate an einsum equation from the given DotDimensionNumber.
std::string CreateEinsumEquation(