File size: 1,623 Bytes
256a159 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 |
from datasets import Dataset, load_dataset
from opencompass.registry import LOAD_DATASET, TEXT_POSTPROCESSORS
from ..base import BaseDataset
@TEXT_POSTPROCESSORS.register_module('gsm100_dataset')
def gsm100_dataset_postprocess(text: str) -> str:
return text.replace(',', '')
@TEXT_POSTPROCESSORS.register_module('gsm100')
def gsm100_postprocess(text: str) -> str:
# text = text.split('\n\n')[0]
segs = text.split('The answer is')
if len(segs) < 2:
return ''
text = segs[1]
text = text.split(' ')
flag = False
ret = ''
for i in range(len(text)):
s = text[i]
for i in range(len(s)):
if s[i].isdigit():
flag = True
ret = s
break
if flag:
break
ret1 = ''
for i in range(len(ret)):
if ret[i].isdigit():
ret1 += ret[i]
return ret1
@LOAD_DATASET.register_module()
class LEvalGSM100Dataset(BaseDataset):
@staticmethod
def load(**kwargs):
dataset = load_dataset(**kwargs)
split = 'test'
raw_data = []
for i in range(len(dataset[split])):
instructions = dataset[split]['instructions'][i]
outputs = dataset[split]['outputs'][i]
context = dataset[split]['input'][i]
for question, answer in zip(instructions, outputs):
raw_data.append({
'question': question,
'context': context,
'answer': answer
})
dataset[split] = Dataset.from_list(raw_data)
return dataset
|