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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>
108 lines
3.8 KiB
Python
108 lines
3.8 KiB
Python
import json
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from datasets import Dataset, 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 WSCDataset(BaseDataset):
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@staticmethod
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def load(**kwargs):
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if 'data_files' in kwargs:
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kwargs['data_files'] = get_data_path(kwargs['data_files'],
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local_mode=True)
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dataset = load_dataset(**kwargs)
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def preprocess(example):
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text_list = example['text'].split(' ')
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assert ' ' not in example['target']['span2_text']
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# span1 may have 1 or more than 1 words
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# span2 is the pronoun and has only 1 word
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text_list[example['target']
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['span2_index']] = example['target']['span1_text']
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example['new_text'] = ' '.join(text_list)
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if example['label'] == 'true':
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example['answer'] = 1
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else:
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example['answer'] = 0
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example['span1'] = example['target']['span1_text']
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example['span2'] = example['target']['span2_text']
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del example['target']
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return example
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dataset = dataset.map(preprocess)
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return dataset
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@LOAD_DATASET.register_module()
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class WSCDatasetV2(BaseDataset):
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@staticmethod
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def load(path):
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path = get_data_path(path, local_mode=True)
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data = []
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with open(path, 'r') as f:
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for line in f:
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line = json.loads(line)
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item = {
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'span1': line['target']['span1_text'],
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'span2': line['target']['span2_text'],
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'text': line['text'],
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'label': {
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'true': 'A',
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'false': 'B'
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}[line['label']],
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}
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data.append(item)
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return Dataset.from_list(data)
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@LOAD_DATASET.register_module()
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class WSCDatasetV3(BaseDataset):
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@staticmethod
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def load(path):
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path = get_data_path(path, local_mode=True)
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data = []
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with open(path, 'r') as f:
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for line in f:
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line = json.loads(line)
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text_list = line['text'].split(' ')
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span_text1_len = len(line['target']['span1_text'].split(' '))
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span_text2_len = len(line['target']['span2_text'].split(' '))
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span1_start = line['target']['span1_index']
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span1_end = span1_start + span_text1_len
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span2_start = line['target']['span2_index']
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span2_end = span2_start + span_text2_len
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new_text_list = []
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for i, t in enumerate(text_list):
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if span1_start <= i < span1_end:
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if i == span1_start:
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new_text_list.append('* ' +
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line['target']['span1_text'] +
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' *')
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elif span2_start <= i < span2_end:
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if i == span2_start:
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new_text_list.append('# ' +
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line['target']['span2_text'] +
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' #')
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else:
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new_text_list.append(t)
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item = {
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'span1': line['target']['span1_text'],
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'span2': line['target']['span2_text'],
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'text': ' '.join(new_text_list),
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'label': {
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'true': 'A',
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'false': 'B'
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}[line['label']],
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}
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data.append(item)
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return Dataset.from_list(data)
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