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skip = *.ipynb | ||
count = | ||
quiet-level = 3 | ||
ignore-words-list = nd, ans, ques | ||
ignore-words-list = nd, ans, ques, rouge |
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name: lint | ||
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on: [push, pull_request] | ||
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concurrency: | ||
group: ${{ github.workflow }}-${{ github.ref }} | ||
cancel-in-progress: true | ||
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jobs: | ||
lint: | ||
runs-on: ubuntu-latest | ||
steps: | ||
- uses: actions/checkout@v3 | ||
- name: Set up Python 3.10 | ||
uses: actions/setup-python@v4 | ||
with: | ||
python-version: '3.10' | ||
- name: Install pre-commit hook | ||
run: | | ||
pip install pre-commit | ||
pre-commit install | ||
- name: Linting | ||
run: pre-commit run --all-files |
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@@ -82,3 +82,6 @@ instance/ | |
# Auto generate documentation | ||
docs/en/_build/ | ||
docs/zh_cn/_build/ | ||
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# .zip | ||
*.zip |
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assign: | ||
issues: enabled | ||
pull_requests: disabled | ||
strategy: | ||
# random | ||
daily-shift-based | ||
scedule: | ||
'*/1 * * * *' | ||
assignees: | ||
- Leymore | ||
- gaotongxiao | ||
- yingfhu | ||
- Ezra-Yu | ||
- tonysy |
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from mmengine.config import read_base | ||
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with read_base(): | ||
from .cmmlu_gen_ffe7c0 import cmmlu_datasets # noqa: F401, F403 |
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from opencompass.openicl.icl_prompt_template import PromptTemplate | ||
from opencompass.openicl.icl_retriever import FixKRetriever | ||
from opencompass.openicl.icl_inferencer import GenInferencer | ||
from opencompass.openicl.icl_evaluator import AccEvaluator | ||
from opencompass.datasets import CMMLUDataset | ||
from opencompass.utils.text_postprocessors import first_capital_postprocess | ||
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cmmlu_subject_mapping = { | ||
'agronomy': '农学', | ||
'anatomy': '解剖学', | ||
'ancient_chinese': '古汉语', | ||
'arts': '艺术学', | ||
'astronomy': '天文学', | ||
'business_ethics': '商业伦理', | ||
'chinese_civil_service_exam': '中国公务员考试', | ||
'chinese_driving_rule': '中国驾驶规则', | ||
'chinese_food_culture': '中国饮食文化', | ||
'chinese_foreign_policy': '中国外交政策', | ||
'chinese_history': '中国历史', | ||
'chinese_literature': '中国文学', | ||
'chinese_teacher_qualification': '中国教师资格', | ||
'clinical_knowledge': '临床知识', | ||
'college_actuarial_science': '大学精算学', | ||
'college_education': '大学教育学', | ||
'college_engineering_hydrology': '大学工程水文学', | ||
'college_law': '大学法律', | ||
'college_mathematics': '大学数学', | ||
'college_medical_statistics': '大学医学统计', | ||
'college_medicine': '大学医学', | ||
'computer_science': '计算机科学', | ||
'computer_security': '计算机安全', | ||
'conceptual_physics': '概念物理学', | ||
'construction_project_management': '建设工程管理', | ||
'economics': '经济学', | ||
'education': '教育学', | ||
'electrical_engineering': '电气工程', | ||
'elementary_chinese': '小学语文', | ||
'elementary_commonsense': '小学常识', | ||
'elementary_information_and_technology': '小学信息技术', | ||
'elementary_mathematics': '初等数学', | ||
'ethnology': '民族学', | ||
'food_science': '食品科学', | ||
'genetics': '遗传学', | ||
'global_facts': '全球事实', | ||
'high_school_biology': '高中生物', | ||
'high_school_chemistry': '高中化学', | ||
'high_school_geography': '高中地理', | ||
'high_school_mathematics': '高中数学', | ||
'high_school_physics': '高中物理学', | ||
'high_school_politics': '高中政治', | ||
'human_sexuality': '人类性行为', | ||
'international_law': '国际法学', | ||
'journalism': '新闻学', | ||
'jurisprudence': '法理学', | ||
'legal_and_moral_basis': '法律与道德基础', | ||
'logical': '逻辑学', | ||
'machine_learning': '机器学习', | ||
'management': '管理学', | ||
'marketing': '市场营销', | ||
'marxist_theory': '马克思主义理论', | ||
'modern_chinese': '现代汉语', | ||
'nutrition': '营养学', | ||
'philosophy': '哲学', | ||
'professional_accounting': '专业会计', | ||
'professional_law': '专业法学', | ||
'professional_medicine': '专业医学', | ||
'professional_psychology': '专业心理学', | ||
'public_relations': '公共关系', | ||
'security_study': '安全研究', | ||
'sociology': '社会学', | ||
'sports_science': '体育学', | ||
'traditional_chinese_medicine': '中医中药', | ||
'virology': '病毒学', | ||
'world_history': '世界历史', | ||
'world_religions': '世界宗教' | ||
} | ||
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cmmlu_all_sets = list(cmmlu_subject_mapping.keys()) | ||
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cmmlu_datasets = [] | ||
for _name in cmmlu_all_sets: | ||
_ch_name = cmmlu_subject_mapping[_name] | ||
cmmlu_infer_cfg = dict( | ||
ice_template=dict( | ||
type=PromptTemplate, | ||
template=dict( | ||
begin="</E>", | ||
round=[ | ||
dict( | ||
role="HUMAN", | ||
prompt= | ||
f"以下是关于{_ch_name}的单项选择题,请直接给出正确答案的选项。\n题目:{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}" | ||
), | ||
dict(role="BOT", prompt='答案是: {answer}'), | ||
]), | ||
ice_token="</E>", | ||
), | ||
retriever=dict(type=FixKRetriever), | ||
inferencer=dict(type=GenInferencer, fix_id_list=[0, 1, 2, 3, 4]), | ||
) | ||
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cmmlu_eval_cfg = dict( | ||
evaluator=dict(type=AccEvaluator), | ||
pred_postprocessor=dict(type=first_capital_postprocess)) | ||
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cmmlu_datasets.append( | ||
dict( | ||
type=CMMLUDataset, | ||
path="./data/cmmlu/", | ||
name=_name, | ||
abbr=f"cmmlu-{_name}", | ||
reader_cfg=dict( | ||
input_columns=["question", "A", "B", "C", "D"], | ||
output_column="answer", | ||
train_split="dev", | ||
test_split='test'), | ||
infer_cfg=cmmlu_infer_cfg, | ||
eval_cfg=cmmlu_eval_cfg, | ||
)) | ||
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del _name, _ch_name |
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from mmengine.config import read_base | ||
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with read_base(): | ||
from .cmmlu_ppl_fd1f2f import cmmlu_datasets # noqa: F401, F403 |
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