code: def label_from_lists(self, train_labels:Iterator, valid_labels:Iterator, label_cls:Callable=None, **kwargs)->'LabelList':
          "Use the labels in `train_labels` and `valid_labels` to label the data. `label_cls` will overwrite the default."
          label_cls = self.train.get_label_cls(train_labels, label_cls)
          self.train = self.train._label_list(x=self.train, y=label_cls(train_labels, **kwargs))
          self.valid = self.valid._label_list(x=self.valid, y=self.train.y.new(valid_labels, **kwargs))
          self.__class__ = LabelLists
          self.process()
          return self label_from_lists(self, train_labels:Iterator, valid_labels:Iterator, label_cls:Callable=None, **kwargs)->'LabelList':
          "Use the labels in `train_labels` and `valid_labels` to label the data. `label_cls` will overwrite the default."
          label_cls = self.train.get_label_cls(train_labels, label_cls)
          self.train = self.train._label_list(x=self.train, y=label_cls(train_labels, **kwargs))
          self.valid = self.valid._label_list(x=self.valid, y=self.train.y.new(valid_labels, **kwargs))
          self.__class__ = LabelLists
          self.process()
          return self
docs: Use the labels in `train_labels` and `valid_labels` to label the data. `label_cls` will overwrite the default.