def get_topics(self, full: bool = False) -> Mapping[str, Tuple[str, float]]:
        """Return topics with top n words and their c-TF-IDF score.

        Arguments:
            full: If True, returns all different forms of topic representations
                  for each topic, including aspects

        Returns:
            self.topic_representations_: The top n words per topic and the corresponding c-TF-IDF score

        Examples:
        ```python
        all_topics = topic_model.get_topics()
        ```
        """
        check_is_fitted(self)

        if full:
            topic_representations = {"Main": self.topic_representations_}
            topic_representations.update(self.topic_aspects_)
            return topic_representations
        else:
            return self.topic_representations_
Return topics with top n words and their c-TF-IDF score.

        Arguments:
            full: If True, returns all different forms of topic representations
                  for each topic, including aspects

        Returns:
            self.topic_representations_: The top n words per topic and the corresponding c-TF-IDF score

        Examples:
        ```python
        all_topics = topic_model.get_topics()
        ```
        
bertopic/_bertopic.py