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* add ceval, gsm8k modelscope surpport * update race, mmlu, arc, cmmlu, commonsenseqa, humaneval and unittest * update bbh, flores, obqa, siqa, storycloze, summedits, winogrande, xsum datasets * format file * format file * update dataset format * support ms_dataset * udpate dataset for modelscope support * merge myl_dev and update test_ms_dataset * udpate dataset for modelscope support * update readme * update eval_api_zhipu_v2 * remove unused code * add get_data_path function * update readme * remove tydiqa japanese subset * add ceval, gsm8k modelscope surpport * update race, mmlu, arc, cmmlu, commonsenseqa, humaneval and unittest * update bbh, flores, obqa, siqa, storycloze, summedits, winogrande, xsum datasets * format file * format file * update dataset format * support ms_dataset * udpate dataset for modelscope support * merge myl_dev and update test_ms_dataset * update readme * udpate dataset for modelscope support * update eval_api_zhipu_v2 * remove unused code * add get_data_path function * remove tydiqa japanese subset * update util * remove .DS_Store * fix md format * move util into package * update docs/get_started.md * restore eval_api_zhipu_v2.py, add environment setting * Update dataset * Update * Update * Update * Update --------- Co-authored-by: Yun lin <yunlin@U-Q9X2K4QV-1904.local> Co-authored-by: Yunnglin <mao.looper@qq.com> Co-authored-by: Yun lin <yunlin@laptop.local> Co-authored-by: Yunnglin <maoyl@smail.nju.edu.cn> Co-authored-by: zhangsongyang <zhangsongyang@pjlab.org.cn>
39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
from datasets import Dataset
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from opencompass.registry import LOAD_DATASET
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from opencompass.utils import get_data_path
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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 InfiniteBenchcodedebugDataset(BaseDataset):
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@staticmethod
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def load(path: str):
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path = get_data_path(path, local_mode=True)
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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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question = item['input']
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option_A = item['options'][0]
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option_B = item['options'][1]
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option_C = item['options'][2]
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option_D = item['options'][3]
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answer = chr(item['options'].index(item['answer'][0]) + ord('A'))
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raw_data.append({
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'context': context,
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'question': question,
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'option_A': option_A,
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'option_B': option_B,
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'option_C': option_C,
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'option_D': option_D,
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'answer': answer
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})
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dataset = Dataset.from_list(raw_data)
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return dataset
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