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34 lines
1.3 KiB
Python
34 lines
1.3 KiB
Python
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from mmengine.config import read_base
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with read_base():
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from .groups.cibench import cibench_summary_groups
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summarizer = dict(
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dataset_abbrs=[
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'######## CIBench Generation ########', # category
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['cibench', 'executable'],
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['cibench', 'general_correct'],
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['cibench', 'vis_sim'],
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'######## CIBench Template ########', # category
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'cibench_template:executable',
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'cibench_template:numeric_correct',
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'cibench_template:text_score',
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'cibench_template:vis_sim',
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'######## CIBench Template Chinese ########', # category
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'cibench_template_cn:executable',
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'cibench_template_cn:numeric_correct',
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'cibench_template_cn:text_score',
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'cibench_template_cn:vis_sim',
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'######## CIBench Template w/o NLTK ########', # category no text score becase it is only for nltk
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'cibench_template_wo_nltk:executable',
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'cibench_template_wo_nltk:numeric_correct',
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'cibench_template_wo_nltk:vis_sim',
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'######## CIBench Template Chinese w/o NLTK ########', # category
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'cibench_template_cn_wo_nltk:executable',
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'cibench_template_cn_wo_nltk:numeric_correct',
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'cibench_template_cn_wo_nltk:vis_sim',
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],
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summary_groups=sum(
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[v for k, v in locals().items() if k.endswith("_summary_groups")], [])
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)
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