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# -*- coding: utf-8 -*-
'''
@Author : Jiangjie Chen
@Time : 2020/7/25 18:23
@Contact : [email protected]
@Description:
'''
import os
import cjjpy as cjj
import sys
import tensorflow as tf
import ujson as json
from tqdm import tqdm
import argparse
try:
sys.path.append(cjj.AbsParentDir(__file__, '..'))
from hparams import *
from pseudo_multiproc_toolkit import *
from dataloaders import FEVERLoader
from parsing_client.sentence_parser import SentenceParser, deal_bracket
from qg_client.question_generator import QuestionGenerator
except:
from .hparams import *
from .pseudo_multiproc_toolkit import *
from ..dataloaders import FEVERLoader
from ..parsing_client.sentence_parser import SentenceParser, deal_bracket
from ..qg_client.question_generator import QuestionGenerator
def prepare_answers(version, role, evi_key='bert_evidence', overwrite=False):
'''
:return
{
'id': id,
'claim': c,
'label': x,
'evidence': [e1, e2, ...], # n
'answers': [a1, a2, ...], # m
'answer_roles': [noun, noun, adj, verb, ...] # m
}
'''
assert role in ['val', 'test', 'train', 'eval'], role
def _proc_one(js):
js.pop('all_evidence')
evidence = [deal_bracket(ev[2], True, ev[0]) for ev in js[evi_key]]
results = sent_client.identify_NPs(deal_bracket(js['claim'], True),
candidate_NPs=[x[0] for x in js[evi_key]])
NPs = results['NPs']
claim = results['text']
verbs = results['verbs']
adjs = results['adjs']
_cache = {'id': js['id'],
'claim': claim,
'evidence': evidence,
'answers': NPs + verbs + adjs,
'answer_roles': ['noun'] * len(NPs) + ['verb'] * len(verbs) + ['adj'] * len(adjs)}
if js.get('label'):
_cache.update({'label': js['label']})
return _cache
cached_ = QG_PREFIX.format(version=version) + CACHED_ANSEWR_FILE.format(role=role)
tf.io.gfile.makedirs(QG_PREFIX.format(version=version))
if tf.io.gfile.exists(cached_) and not overwrite:
print(f'* Skipped, exising {cached_}')
return cached_
sent_client = SentenceParser(device='cuda:0')
floader = FEVERLoader(role)
floader.load_fever(evi_key.split('_')[0])
with tf.io.gfile.GFile(cached_, 'w') as f:
for id in tqdm(floader, desc=f'{role} answer'):
res = _proc_one(floader[id])
f.write(json.dumps(res) + '\n')
cjj.lark(f'* NPs baked in {cached_}')
return cached_
def prepare_questions(version, role, qg_model='t5', batch_size=64, overwrite=False):
'''
After prepare_nps
:return
{
'id': id,
'claim': c,
'label': x,
'evidence': [e1, e2, ...], # n
'answers': [a1, a2, ...], # m
'questions': [q1, q2, ...], # m
'cloze_qs': [q1, q2, ...], #m
'regular_qs': [q1, q2, ...], #m
'answer_roles': [noun, noun, adj, verb, ...] # m
}
'''
cached_answer = QG_PREFIX.format(version=version) + CACHED_ANSEWR_FILE.format(role=role)
cached_question = QG_PREFIX.format(version=version) + CACHED_QUESTION_FILE.format(role=role)
if tf.io.gfile.exists(cached_question) and not overwrite:
print(f'* Skipped, existing {cached_question}')
return cached_question
qg_client = QuestionGenerator(qg_model)
with tf.io.gfile.GFile(cached_answer, 'r') as f, \
tf.io.gfile.GFile(cached_question, 'w') as fo:
data = f.read().splitlines()
data_dict = {}
_cache = []
for line in data:
js = json.loads(line)
data_dict[js['id']] = js
if len(js['answers']) == 0:
# TODO: hack empty answer
print('Empty answer:', js)
pseudo_answer = js['claim'].split()[0]
js['answers'] = [(pseudo_answer, 0, len(pseudo_answer))]
js['answer_roles'] = ['noun']
for answer in js['answers']:
_cache.append((js['claim'], [answer], js['id']))
print(_cache[:5])
qa_pairs = qg_client.generate([(x, y) for x, y, z in _cache], batch_size=batch_size)
print(qa_pairs[:5])
for (q, clz_q, a), (_, _, id) in zip(qa_pairs, _cache):
if 'questions' in data_dict[id]:
data_dict[id]['cloze_qs'].append(clz_q)
data_dict[id]['regular_qs'].append(q)
data_dict[id]['questions'].append(qg_client.assemble_question(q, clz_q))
else:
data_dict[id]['cloze_qs'] = [clz_q]
data_dict[id]['regular_qs'] = [q]
data_dict[id]['questions'] = [qg_client.assemble_question(q, clz_q)]
_ = [_sanity_check(data_dict[k]) for k in data_dict]
for k in data_dict:
fo.write(json.dumps(data_dict[k]) + '\n')
cjj.lark(f'* Questions baked in {cached_question}')
return cached_question
def _sanity_check(js):
try:
assert len(js['questions']) == len(js['answers'])
assert len(js['answers']) == len(js['answer_roles'])
except:
print(js)
raise Exception
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--overwrite', action='store_true')
parser.add_argument('--batch_size', '-b', type=int, default=64)
parser.add_argument('--evi_key', '-e', type=str, default='bert_evidence')
parser.add_argument('--version', '-v', type=str, help='v1, v2, ...', default='v5')
parser.add_argument('--roles', nargs='+', required=True,
help='train val test eval')
parser.add_argument('--qg_model', '-m', type=str, default='t5')
args = parser.parse_args()
for role in args.roles:
prepare_answers(args.version, role, args.evi_key, args.overwrite)
prepare_questions(args.version, role, args.qg_model, args.batch_size, args.overwrite)
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