def __call__(self, contexts_raw: Tuple[str, ...], questions_raw: Tuple[str, ...],<EOL>**kwargs) -> Tuple[<EOL>List[str], List[List[str]], List[List[List[str]]],<EOL>List[List[int]], List[List[int]],<EOL>List[str], List[List[str]], List[List[List[str]]],<EOL>List[List[Tuple[int, int]]]<EOL>]:
contexts = []<EOL>contexts_tokens = []<EOL>contexts_chars = []<EOL>contexts_r2p = []<EOL>contexts_p2r = []<EOL>questions = []<EOL>questions_tokens = []<EOL>questions_chars = []<EOL>spans = []<EOL>for c_raw, q_raw in zip(contexts_raw, questions_raw):<EOL><INDENT>c, r2p, p2r = SquadPreprocessor.preprocess_str(c_raw, return_mapping=True)<EOL>c_tokens = [token.replace("<STR_LIT>", '<STR_LIT:">').replace("<STR_LIT>", '<STR_LIT:">') for token in word_tokenize(c)][:self.context_limit]<EOL>c_chars = [list(token)[:self.char_limit] for token in c_tokens]<EOL>q = SquadPreprocessor.preprocess_str(q_raw)<EOL>q_tokens = [token.replace("<STR_LIT>", '<STR_LIT:">').replace("<STR_LIT>", '<STR_LIT:">') for token in word_tokenize(q)][:self.question_limit]<EOL>q_chars = [list(token)[:self.char_limit] for token in q_tokens]<EOL>contexts.append(c)<EOL>contexts_tokens.append(c_tokens)<EOL>contexts_chars.append(c_chars)<EOL>contexts_r2p.append(r2p)<EOL>contexts_p2r.append(p2r)<EOL>questions.append(q)<EOL>questions_tokens.append(q_tokens)<EOL>questions_chars.append(q_chars)<EOL>spans.append(SquadPreprocessor.convert_idx(c, c_tokens))<EOL><DEDENT>return contexts, contexts_tokens, contexts_chars, contexts_r2p, contexts_p2r,questions, questions_tokens, questions_chars, spans<EOL>
Performs preprocessing of context and question
        Args:
            contexts_raw: batch of contexts to preprocess
            questions_raw: batch of questions to preprocess

        Returns:
            context: batch of processed contexts
            contexts_tokens: batch of tokenized contexts
            contexts_chars: batch of tokenized and split on chars contexts
            contexts_r2p: batch of mappings from raw context to processed context
            contexts_p2r: batch of mappings from procesesd context to raw context
            questions: batch of processed questions
            questions_tokens: batch of tokenized questions
            questions_chars: batch of tokenized and split on chars questions
            spans: batch of mapping tokens to position in context