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* add InfiniteBench * add InfiniteBench --------- Co-authored-by: wangchonghua <wangchonghua@pjlab.org.cn>
55 lines
1.5 KiB
Python
55 lines
1.5 KiB
Python
import re
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from typing import List
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from datasets import Dataset
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from opencompass.openicl import BaseEvaluator
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from opencompass.registry import ICL_EVALUATORS, LOAD_DATASET
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from ..base import BaseDataset
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from .utils import iter_jsonl
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@LOAD_DATASET.register_module()
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class InfiniteBenchmathcalcDataset(BaseDataset):
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@staticmethod
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def load(path: str):
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dataset = list(iter_jsonl(path))
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raw_data = []
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for item in dataset:
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context = item['context']
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answer = item['answer']
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raw_data.append({'context': context, 'answer': answer})
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dataset = Dataset.from_list(raw_data)
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return dataset
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@ICL_EVALUATORS.register_module()
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class InfiniteBenchmathcalcEvaluator(BaseEvaluator):
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def score(self, predictions: List, references: List) -> dict:
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score = 0.
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for i in range(len(predictions)):
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prediction = predictions[i]
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reference = references[i]
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prediction_nums = []
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prediction_list = re.split('[^0-9]', prediction)
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for item in prediction_list:
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if item != '':
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prediction_nums.append(int(item))
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for j in range(len(reference)):
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if j >= len(prediction_nums):
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break
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if reference[j] == prediction_nums[j]:
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score += 1
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else:
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break
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score = score / len(predictions) * 100
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return {'score': score}
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