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main_threads.py
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main_threads.py
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import json
import logging
import threading
from collections import Counter
import openai
from config import args
from extracter import extract_answer, get_precision
from prompt import get_prompt, construct_input
from prediction_runner import basic_runner
from utils import write_json, print_now, mkpath, print_exp, load_data
now = print_now(1).split(' ')[0].replace('/', '-')
Result_Folder = 'result/{}'.format(now)
mkpath('result')
mkpath(Result_Folder)
mkpath(f'{Result_Folder}/{args.dataset}')
Log_Folder = 'log/{}'.format(now)
mkpath('log')
mkpath(Log_Folder)
mkpath(f'{Log_Folder}/{args.dataset}')
Decoder_Error_File = f'{Result_Folder}/{args.learning_type}-{args.dataset}-{args.prompt_id}-{args.engine}-SC-{args.SC}_deco.json'
Predict_File = f'{Result_Folder}/{args.dataset}/{args.learning_type}-{args.prompt_id}-{args.engine}-SC-{args.SC}.json'
Log_File = f'{Log_Folder}/{args.dataset}/{args.learning_type}-{args.prompt_id}-{args.engine}-SC-{args.SC}.log'
# logging.basicConfig(filename=Log_File)
formatter = logging.Formatter('%(asctime)s - %(pathname)s[line:%(lineno)d] - %(levelname)s: %(message)s')
sh = logging.StreamHandler()
fh = logging.FileHandler(filename=Log_File)
fh.setFormatter(formatter)
sh.setFormatter(formatter)
logger = logging.getLogger()
logger.addHandler(fh)
logger.addHandler(sh)
Decoder_Error_File_Lock = threading.Lock()
Predict_File_Lock = threading.Lock()
API_File_Lock = threading.Lock()
Correct_Lock = threading.Lock()
Total_Lock = threading.Lock()
Global_Correct = 0
Global_Total = 0
def thread_task(datas: tuple, args, thread_id, apikey):
correct = 0
global Global_Correct
global Global_Total
question, answer, ids = datas
_, prompt = get_prompt()
for idx, element in enumerate(question):
# --test_star 100 从100开始测试
# --test_end 100 只测前100个
# --test_star 100 --test_end 200 从100开始测试，到200结束
inputs = construct_input(prompt, element)
try:
get_result, pred, error_msg = basic_runner(args, inputs, args.max_length_cot, apikey)
except Exception as e:
decode_error_data = {
'question': question[idx]
}
Decoder_Error_File_Lock.acquire()
write_json(decode_error_data, Decoder_Error_File)
Decoder_Error_File_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
logger.warning(
f"an error raised when predicting (question id: {ids[idx]}). "
f"ERROR: {getattr(e.__class__, '__name__')}:{str(e)}"
)
continue
if not get_result:
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
logger.warning(
f"not get predicted result (question id: {ids[idx]})."
f"ERROR Message: {error_msg if error_msg else None}"
)
continue
if args.SC:
answer_list = []
for i in range(len(pred)):
input_ = inputs + pred[i]
if 'Therefore, the answer is' in input_ or 'The answer is' in input_:
if 'The answer is' in input_:
input_2 = input_.split('The answer is')[-1]
else:
input_2 = input_.split('the answer is')[-1]
try:
pred_answer1 = extract_answer(args, input_2)
except:
pred_answer1 = None
else:
inputs2 = input_ + ' ' + args.direct_answer_trigger_for_direct
try:
get_result, pred3, error_msg = basic_runner(args, inputs2, 32, apikey)
except Exception as e:
decode_error_data = {
'question': question[idx]
}
Decoder_Error_File_Lock.acquire()
write_json(decode_error_data, Decoder_Error_File)
Decoder_Error_File_Lock.release()
logger.warning(
f"an error raised when predicting (question id: {ids[idx]}). "
f"ERROR: {getattr(e.__class__, '__name__')}:{str(e)}"
)
continue
if not get_result:
logger.warning(
f"not get predicted result (question id: {ids[idx]})."
f"ERROR Message: {error_msg if error_msg else None}"
)
continue
try:
pred_answer1 = extract_answer(args, pred3)
except:
pred_answer1 = None
answer_list.append(pred_answer1)
collection_words = Counter(answer_list)
if collection_words:
pred_answer = collection_words.most_common(1)[0][0]
else:
pred_answer = None
else:
if 'Therefore, the answer is' in pred or 'The answer is' in pred:
if 'The answer is' in pred:
pred2 = pred.split('The answer is')[-1]
else:
pred2 = pred.split('the answer is')[-1]
try:
pred_answer = extract_answer(args, pred2)
except:
pred_answer = None
else:
inputs2 = inputs + pred + ' ' + args.direct_answer_trigger_for_direct
try:
get_result, pred3, error_msg = basic_runner(args, inputs2, 32, apikey)
except Exception as e:
decode_error_data = {
'question': question[idx]
}
Decoder_Error_File_Lock.acquire()
write_json(decode_error_data, Decoder_Error_File)
Decoder_Error_File_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
logger.warning(
f"an error raised when predicting (question id: {ids[idx]}). "
f"ERROR: {getattr(e.__class__, '__name__')}:{str(e)}"
)
continue
if not get_result:
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
logger.warning(
f"not get predicted result (question id: {ids[idx]})."
f"ERROR Message: {error_msg if error_msg else None}"
)
continue
try:
pred_answer = extract_answer(args, pred3)
except:
pred_answer = None
ans = False
if pred_answer is not None:
if args.dataset.lower() in ["svamp", "gsm8k", "multiarith", "addsub", "singleeq"]:
if abs(pred_answer - answer[idx]) < 1e-3:
correct += 1
ans = True
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Correct_Lock.acquire()
Global_Correct += 1
Correct_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
else:
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
else:
if isinstance(pred_answer, float) and isinstance(answer[idx], float):
precision = min(get_precision(pred_answer), get_precision(answer[idx]))
if round(pred_answer, precision) == round(answer[idx], precision):
correct += 1
ans = True
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Correct_Lock.acquire()
Global_Correct += 1
Correct_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
else:
ans = False
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
else:
if pred_answer == answer[idx]:
correct += 1
ans = True
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Correct_Lock.acquire()
Global_Correct += 1
Correct_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
else:
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
else:
json_data = {
"ID": ids[idx],
"question": question[idx],
"chain-of-thought": pred,
"pred": pred_answer,
"answer": answer[idx],
"ans": ans
}
Predict_File_Lock.acquire()
write_json(json_data, Predict_File)
Predict_File_Lock.release()
Total_Lock.acquire()
Global_Total += 1
Total_Lock.release()
logger.info(
f"thread:{thread_id} | correct:{correct} tested:{idx + 1} {correct / (idx + 1)} total:{len(question)} | "
f"global correct/total:{Global_Correct}/{Global_Total}"
)
return correct
def zero_shot_cot():
correct = 0
question, answer, ids = load_data(args)
avr_nums = int(len(question) / 8)
thread_list = []
apikey_list = json.load(open('apikeys.json', 'r', encoding='utf-8'))
assert len(apikey_list) >= 8, f"need 8 apikeys, find {len(apikey_list)} in '/apikeys.json'"
for i in range(8):
if i == 7:
thread_list.append(
TaskThread(
str(i),
datas=(question[i * avr_nums:], answer[i * avr_nums:],
ids[i * avr_nums:]),
args=args,
apikey=apikey_list[i]
)
)
else:
thread_list.append(
TaskThread(
str(i),
datas=(question[i * avr_nums:(i + 1) * avr_nums], answer[i * avr_nums:(i + 1) * avr_nums],
ids[i * avr_nums:(i + 1) * avr_nums]),
args=args,
apikey=apikey_list[i]
)
)
for i in range(8):
thread_list[i].start()
for i in range(8):
thread_list[i].join()
for i in range(8):
correct += thread_list[i].result
return correct
class TaskThread(threading.Thread):
def __init__(self, thread_id, datas, args, apikey):
super().__init__(None)
self.thread_id = thread_id
self.datas = datas
self.args = args
self.result = None
self.apikey = apikey
def run(self) -> None:
self.result = thread_task(self.datas, self.args, self.thread_id, self.apikey)
if __name__ == '__main__':
print_exp(args)
alls = zero_shot_cot()
logger.info(f"correct num: {alls}")