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