def train(self, iterator: Union[DataFittingIterator, DataLearningIterator]) -> None:
        """Calls :meth:`~fit_chainer` with provided data iterator as an argument"""
        self.fit_chainer(iterator)
        self._saved = True
Calls :meth:`~fit_chainer` with provided data iterator as an argument
deeppavlov/core/trainers/fit_trainer.py