def encode(
        self, sentence: str, *addl_sentences, no_separator=True
    ) -> torch.LongTensor:
        tokens = self.bpe.encode(sentence)
        if len(tokens.split(" ")) > min(self.max_positions) - 2:
            tokens = " ".join(tokens.split(" ")[: min(self.max_positions) - 2])
        bpe_sentence = "<s> " + tokens + " </s>"
        for s in addl_sentences:
            bpe_sentence += " </s>" if not no_separator else ""
            bpe_sentence += " " + self.bpe.encode(s) + " </s>"
        tokens = self.task.source_dictionary.encode_line(bpe_sentence, append_eos=False) # Always add OOV token as new type
        return tokens.long()

    def encode(
        self, 
        sentence: str, 
        *addl_sentences, 
        no_separator=True,
        add_if_not_exist=True # Add an extra option
    ) -> torch.LongTensor:
        tokens = self.bpe.encode(sentence)
        if len(tokens.split(" ")) > min(self.max_positions) - 2:
            tokens = " ".join(tokens.split(" ")[: min(self.max_positions) - 2])
        bpe_sentence = "<s> " + tokens + " </s>"
        for s in addl_sentences:
            bpe_sentence += " </s>" if not no_separator else ""
            bpe_sentence += " " + self.bpe.encode(s) + " </s>"
        tokens = self.task.source_dictionary.encode_line(
            bpe_sentence, append_eos=False, add_if_not_exist=add_if_not_exist
        )
        return tokens.long()