debug_info_file,        xla_compile_device_type,
      prune_unused_nodes,     convert_legacy_fed_inputs,
      graph_as_function,      upgrade_legacy,
      enable_shape_inference, unconditionally_use_set_output_shapes,
      enable_soft_placement,  set_original_tf_func_name};

  auto module_or = tensorflow::GraphdefToMlirTranslateFunction(
      input, input_arrays, input_dtypes, input_shapes, output_arrays,

  std::string xla_compile_device_type;
  bool prune_unused_nodes;
  bool convert_legacy_fed_inputs;
  bool graph_as_function;
  bool upgrade_legacy;
  bool enable_shape_inference;
  bool unconditionally_use_set_output_shapes;
  bool enable_soft_placement;
  bool set_original_tf_func_name = false;
};

// TODO(antiagainst): Directly manipulating files in library functions is not

absl::StatusOr<mlir::OwningOpRef<mlir::ModuleOp>> ConvertSavedModelV1ToMlirLite(
    SavedModelMLIRImportInput& input,
    std::optional<absl::Span<const std::string>> exported_names,
    mlir::MLIRContext* context,
    bool unconditionally_use_set_output_shapes = false);

// Serialize a MLIR module to a string.
std::string MlirModuleToString(mlir::ModuleOp module,
                               mlir::OpPrintingFlags flags);