def to_sentence()

in torchmoji/sentence_tokenizer.py [0:0]

• 5 lines of code
• 5 McCabe index (conditional complexity)

    def to_sentence(self, sentence_idx):
        """ Converts a tokenized sentence back to a list of words.

        # Arguments:
            sentence_idx: List of numbers, representing a tokenized sentence
                given the current vocabulary.

        # Returns:
            String created by converting all numbers back to words and joined
            together with spaces.
        """
        # Have to recalculate the mappings in case the vocab was extended.
        ind_to_word = {ind: word for word, ind in self.vocabulary.items()}

        sentence_as_list = [ind_to_word[x] for x in sentence_idx]
        cleaned_list = [x for x in sentence_as_list if x != 'CUSTOM_MASK']
        return " ".join(cleaned_list)