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from typing import List
from datasets import Dataset
from opencompass.openicl import BaseEvaluator
from opencompass.registry import ICL_EVALUATORS, LOAD_DATASET
from ..base import BaseDataset
from .utils import iter_jsonl
@LOAD_DATASET.register_module()
class InfiniteBenchretrievekvDataset(BaseDataset):
@staticmethod
def load(path: str):
dataset = list(iter_jsonl(path))
raw_data = []
for item in dataset:
context = item['context']
input = item['input']
answer = item['answer']
raw_data.append({
'context': context,
'input': input,
'answer': answer
})
dataset = Dataset.from_list(raw_data)
return dataset
@ICL_EVALUATORS.register_module()
class InfiniteBenchretrievekvEvaluator(BaseEvaluator):
def score(self, predictions: List, references: List) -> dict:
score = 0.
for i in range(len(predictions)):
prediction = predictions[i]
reference = references[i]
for c in ['\n', ':', '\"', '\'', '.', ',', '?', '!', '{', '}']:
prediction = prediction.replace(c, ' ')
words = prediction.split()
if reference in words:
score += 1
score = score / len(predictions) * 100
return {'score': score}
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