code: def as_ordered_dict(self, preference_orders: List[List[str]] = None) -> OrderedDict:
          
          params_dict = self.as_dict(quiet=True)
          if not preference_orders:
              preference_orders = []
              preference_orders.append(["dataset_reader", "iterator", "model",
                                        "train_data_path", "validation_data_path", "test_data_path",
                                        "trainer", "vocabulary"])
              preference_orders.append(["type"])
  
          def order_func(key):
              # Makes a tuple to use for ordering.  The tuple is an index into each of the `preference_orders`,
              # followed by the key itself.  This gives us integer sorting if you have a key in one of the
              # `preference_orders`, followed by alphabetical ordering if not.
              order_tuple = [order.index(key) if key in order else len(order) for order in preference_orders]
              return order_tuple + [key]
  
          def order_dict(dictionary, order_func):
              # Recursively orders dictionary according to scoring order_func
              result = OrderedDict()
              for key, val in sorted(dictionary.items(), key=lambda item: order_func(item[0])):
                  result[key] = order_dict(val, order_func) if isinstance(val, dict) else val
              return result
  
          return order_dict(params_dict, order_func)
docs: Returns Ordered Dict of Params from list of partial order preferences.
  
          Parameters
          ----------
          preference_orders: List[List[str]], optional
              ``preference_orders`` is list of partial preference orders. ["A", "B", "C"] means
              "A" > "B" > "C". For multiple preference_orders first will be considered first.
              Keys not found, will have last but alphabetical preference. Default Preferences:
              ``[["dataset_reader", "iterator", "model", "train_data_path", "validation_data_path",
              "test_data_path", "trainer", "vocabulary"], ["type"]]``