def __call__(self, record_index, question_id, question, context, answer_list,<EOL>answer_start_list):
question_words = self._word_vocab[question.split()[<EOL>:self._question_max_length]]<EOL>context_words = self._word_vocab[context.split()[<EOL>:self._context_max_length]]<EOL>question_chars = [self._char_vocab[list(iter(word))]<EOL>for word in question.split()[:self._question_max_length]]<EOL>context_chars = [self._char_vocab[list(iter(word))]<EOL>for word in context.split()[:self._context_max_length]]<EOL>question_words_nd = nd.array(question_words, dtype=np.int32)<EOL>question_chars_nd = self._padder(question_chars)<EOL>context_words_nd = nd.array(context_words, dtype=np.int32)<EOL>context_chars_nd = self._padder(context_chars)<EOL>answer_spans = SQuADTransform._get_answer_spans(<EOL>answer_list, answer_start_list)<EOL>return record_index, question_id, question_words_nd, context_words_nd,question_chars_nd, context_chars_nd, answer_spans<EOL>
Method converts text into numeric arrays based on Vocabulary.
Answers are not processed, as they are not needed in input