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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def return_labels(self, original=False):
 """ Returns the labels of the dataset Parameters original : if True, will return original labels, if False, will return transformed labels (as defined by label_dict), default value: False Returns ------- A list of lists, each 'inside list' corresponds to a single data point, each element of the 'inside list' is a label """

        if self._prepopulated is False:
            raise errors.EmptyDatabase(self.dbpath)
        else:
            engine = create_engine('sqlite:////' + self.dbpath)
            trainset.Base.metadata.create_all(engine)
            session_cl = sessionmaker(bind=engine)
            session = session_cl()
            return_list = []
            for i in session.query(trainset.TrainSet).order_by(trainset.TrainSet.id):
                if original is True:
                    row_list = i.labels['original']
                else:
                    row_list = i.labels['transformed']
                return_list.append(row_list[:])
            session.close()
            return return_list