def METHOD_NAME(self, texts, language=Languages.ENGLISH, vectorizer=None):
    if self.representation_type == RepresentationType.BOW:
        if vectorizer is None:
            vectorizer = CountVectorizer(analyzer="word", tokenizer=None, preprocessor=None, stop_words=None,
                                         lowercase=True, max_features=1000)
            train_data_features = vectorizer.fit_transform(texts)
            return train_data_features, vectorizer
        else:
            return vectorizer.transform(texts), None
    elif self.representation_type == RepresentationType.WORD_EMBEDDING:
        return self.sentence_embedding_service.get_sentence_embeddings_representation(texts, language=language), None