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edab1c07ba
* 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>
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import os.path as osp
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from typing import List
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from datasets import load_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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@LOAD_DATASET.register_module()
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class InferencePPLDataset(BaseDataset):
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@staticmethod
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def load(path: str, name: List[str] = None, samples: int = None):
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path = get_data_path(path, local_mode=True)
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# Check if file exists in the given path
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supported_extensions = ['jsonl']
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for ext in supported_extensions:
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filename = osp.join(
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path, f'{name}.{ext}') # name refers to data subset name
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if osp.exists(filename):
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break
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else:
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raise FileNotFoundError(f'{filename} not found.')
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samples = 'test' if samples is None else f'test[:{samples}]'
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data_files = {'test': filename}
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dataset = load_dataset('json', data_files=data_files, split=samples)
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# Filter out empty samples
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dataset = dataset.filter(lambda example: len(example['text']) > 0)
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return dataset
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