def document_encoder(title: str, doc_sents: list,
tokenizer: LongformerTokenizer):
title_res = SPECIAL_TITLE_START + title + SPECIAL_TITLE_END ##
title_tokens = tokenizer.tokenize(text=title_res)
title_encode_ids = tokenizer.encode(text=title_tokens,
add_special_tokens=False)
assert len(title_tokens) == len(title_encode_ids)
title_len = len(title_encode_ids)
##++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
encode_id_lens = []
encode_id_lens.append(title_len)
doc_encode_id_list = []
doc_encode_id_list.append(title_encode_ids)
for sent_idx, sent_text in enumerate(doc_sents):
sent_text_res = sent_text + SPECIAL_SENTENCE_TOKEN
sent_tokens = tokenizer.tokenize(text=sent_text_res)
sent_encode_ids = tokenizer.encode(text=sent_tokens,
add_special_tokens=False)
assert len(sent_tokens) == len(sent_encode_ids)
##++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
doc_encode_id_list.append(sent_encode_ids)
sent_len = len(sent_encode_ids)
encode_id_lens.append(sent_len)
##++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
doc_sent_len_cum_list = list(
itertools.accumulate(encode_id_lens, operator.add))
sent_start_end_pair = [(doc_sent_len_cum_list[i],
doc_sent_len_cum_list[i + 1] - 1)
for i in range(len(encode_id_lens) - 1)]
doc_encode_ids = list(itertools.chain.from_iterable(doc_encode_id_list))
assert len(doc_encode_ids) == doc_sent_len_cum_list[-1]
assert len(sent_start_end_pair) == len(doc_sents)
return doc_encode_ids, sent_start_end_pair, len(doc_encode_ids), title_len
def answer_span_token_finder(norm_answer: str, sentence: str,
tokenizer: LongformerTokenizer):
answer_encode_ids = tokenizer.encode(text=norm_answer,
add_special_tokens=False)
sentence_encode_ids = tokenizer.encode(text=sentence,
add_special_tokens=False)
idx = sub_list_finder(target=answer_encode_ids, source=sentence_encode_ids)
flag = idx >= 0
return flag, answer_encode_ids, sentence_encode_ids
def query_encoder(query: str, tokenizer: LongformerTokenizer):
query_res = CLS_TOKEN + SPECIAL_QUERY_START + query + SPECIAL_QUERY_END
query_tokens = tokenizer.tokenize(text=query_res)
query_encode_ids = tokenizer.encode(text=query_tokens, add_special_tokens=False)
assert len(query_tokens) == len(query_encode_ids)
query_len = len(query_encode_ids)
return query_encode_ids, query_len
