Initial commit

opencompass/configs/datasets/FewCLUE_cluewsc/FewCLUE_cluewsc_ppl_868415.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CluewscDataset
+
+cluewsc_reader_cfg = dict(
+    input_columns=['span1', 'span2', 'text', 'new_text'],
+    output_column='answer')
+
+cluewsc_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0:
+            dict(round=[
+                dict(
+                    role='HUMAN',
+                    prompt='{text}\n此处，代词“{span2}“被用于指代“{span1}“吗?'),
+                dict(role='BOT', prompt='否')
+            ]),
+            1:
+            dict(round=[
+                dict(
+                    role='HUMAN',
+                    prompt='{text}\n此处，代词“{span2}“被用于指代“{span1}“吗?'),
+                dict(role='BOT', prompt='是')
+            ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+cluewsc_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+cluewsc_datasets = [
+    dict(
+        type=CluewscDataset,
+        path='json',
+        abbr='cluewsc-dev',
+        data_files='./data/FewCLUE/cluewsc/dev_few_all.json',
+        split='train',
+        reader_cfg=cluewsc_reader_cfg,
+        infer_cfg=cluewsc_infer_cfg,
+        eval_cfg=cluewsc_eval_cfg),
+    dict(
+        type=CluewscDataset,
+        path='json',
+        abbr='cluewsc-test',
+        data_files='./data/FewCLUE/cluewsc/test_public.json',
+        split='train',
+        reader_cfg=cluewsc_reader_cfg,
+        infer_cfg=cluewsc_infer_cfg,
+        eval_cfg=cluewsc_eval_cfg),
+]

opencompass/configs/datasets/FewCLUE_csl/FewCLUE_csl_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_csl_gen_28b223 import csl_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_csl/FewCLUE_csl_gen_28b223.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CslDatasetV2
+from opencompass.utils.text_postprocessors import first_capital_postprocess
+
+csl_reader_cfg = dict(
+    input_columns=['abst', 'keywords'],
+    output_column='label',
+)
+
+csl_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role='HUMAN',
+                prompt=
+                '摘要是对论文内容不加注释和评论的简短陈述，要求扼要地说明研究工作的目的、研究方法和最终结论等。\n关键词是一篇学术论文的核心词汇，一般由一系列名词组成。关键词在全文中应有较高出现频率，且能起到帮助文献检索的作用。\n摘要：{abst}\n关键词：{keywords}\n请问上述关键词是否匹配摘要且符合要求？\nA. 否\nB. 是\n请从”A“，”B“中进行选择。\n答：'
+            )
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+csl_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role='BOT',
+    pred_postprocessor=dict(type=first_capital_postprocess),
+)
+
+csl_datasets = [
+    dict(
+        abbr='csl_dev',
+        type=CslDatasetV2,
+        path='./data/FewCLUE/csl/dev_few_all.json',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg,
+    ),
+    dict(
+        abbr='csl_test',
+        type=CslDatasetV2,
+        path='./data/FewCLUE/csl/test_public.json',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg,
+    ),
+]

opencompass/configs/datasets/FewCLUE_csl/FewCLUE_csl_gen_87f4a8.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CslDatasetV2
+from opencompass.utils.text_postprocessors import first_capital_postprocess
+
+csl_reader_cfg = dict(
+    input_columns=['abst', 'keywords'],
+    output_column='label',
+)
+
+csl_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role='HUMAN',
+                prompt=
+                '摘要：{abst}\n关键词：{keywords}\n上述关键词出现在学术期刊中是否恰当？\nA. 否\nB. 是\n请从”A“，”B“中进行选择。\n答：'
+            )
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+csl_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role='BOT',
+    pred_postprocessor=dict(type=first_capital_postprocess),
+)
+
+csl_datasets = [
+    dict(
+        abbr='csl_dev',
+        type=CslDatasetV2,
+        path='./data/FewCLUE/csl/dev_few_all.json',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg,
+    ),
+    dict(
+        abbr='csl_test',
+        type=CslDatasetV2,
+        path='./data/FewCLUE/csl/test_public.json',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg,
+    ),
+]

opencompass/configs/datasets/FewCLUE_csl/FewCLUE_csl_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_csl_ppl_841b62 import csl_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_csl/FewCLUE_csl_ppl_769f8d.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CslDataset
+
+csl_reader_cfg = dict(
+    input_columns=['abst', 'keywords'], output_column='label')
+
+csl_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0:
+            dict(round=[dict(role='HUMAN', prompt='摘要：{abst}')]),
+            1:
+            dict(
+                round=[dict(role='HUMAN', prompt='摘要：{abst}\n关键词：{keywords}')
+                       ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+csl_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+csl_datasets = [
+    dict(
+        type=CslDataset,
+        path='json',
+        abbr='csl_dev',
+        data_files='./data/FewCLUE/csl/dev_few_all.json',
+        split='train',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg),
+    dict(
+        type=CslDataset,
+        path='json',
+        abbr='csl_test',
+        data_files='./data/FewCLUE/csl/test_public.json',
+        split='train',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg)
+]

opencompass/configs/datasets/FewCLUE_csl/FewCLUE_csl_ppl_841b62.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CslDataset
+
+csl_reader_cfg = dict(
+    input_columns=['abst', 'keywords'], output_column='label')
+
+csl_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0: '摘要：{abst}',
+            1: '摘要：{abst}\n关键词：{keywords}'
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+csl_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+csl_datasets = [
+    dict(
+        type=CslDataset,
+        path='json',
+        abbr='csl_dev',
+        data_files='./data/FewCLUE/csl/dev_few_all.json',
+        split='train',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg),
+    dict(
+        type=CslDataset,
+        path='json',
+        abbr='csl_test',
+        data_files='./data/FewCLUE/csl/test_public.json',
+        split='train',
+        reader_cfg=csl_reader_cfg,
+        infer_cfg=csl_infer_cfg,
+        eval_cfg=csl_eval_cfg)
+]

opencompass/configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_eprstmt_gen_740ea0 import eprstmt_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_gen_740ea0.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import EprstmtDatasetV2
+from opencompass.utils.text_postprocessors import first_capital_postprocess
+
+eprstmt_reader_cfg = dict(
+    input_columns=['sentence'], output_column='label', test_split='train')
+
+eprstmt_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role='HUMAN',
+                prompt=
+                '内容： "{sentence}"。请对上述内容进行情绪分类。\nA. 积极\nB. 消极\n请从”A“，”B“中进行选择。\n答：'
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+eprstmt_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role='BOT',
+    pred_postprocessor=dict(type=first_capital_postprocess),
+)
+
+eprstmt_datasets = [
+    dict(
+        abbr='eprstmt-dev',
+        type=EprstmtDatasetV2,
+        path='./data/FewCLUE/eprstmt/dev_few_all.json',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg,
+    ),
+    dict(
+        abbr='eprstmt-test',
+        type=EprstmtDatasetV2,
+        path='./data/FewCLUE/eprstmt/test_public.json',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg,
+    ),
+]

opencompass/configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_eprstmt_ppl_f1e631 import eprstmt_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_ppl_1ce587.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+eprstmt_reader_cfg = dict(
+    input_columns=['sentence'], output_column='label', test_split='train')
+
+eprstmt_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'Negative': ' 内容： "{sentence}"。情绪分类：消极。',
+            'Positive': ' 内容： "{sentence}"。情绪分类：积极。',
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+eprstmt_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+eprstmt_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='eprstmt-dev',
+        path='json',
+        data_files='./data/FewCLUE/eprstmt/dev_few_all.json',
+        split='train',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg),
+    dict(
+        type=HFDataset,
+        abbr='eprstmt-test',
+        path='json',
+        data_files='./data/FewCLUE/eprstmt/test_public.json',
+        split='train',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg)
+]

opencompass/configs/datasets/FewCLUE_eprstmt/FewCLUE_eprstmt_ppl_f1e631.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+eprstmt_reader_cfg = dict(
+    input_columns=['sentence'], output_column='label', test_split='train')
+
+eprstmt_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'Negative':
+            dict(round=[
+                dict(role='HUMAN', prompt='内容： "{sentence}"。情绪分类：'),
+                dict(role='BOT', prompt='消极。')
+            ]),
+            'Positive':
+            dict(round=[
+                dict(role='HUMAN', prompt='内容： "{sentence}"。情绪分类：'),
+                dict(role='BOT', prompt='积极。')
+            ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+eprstmt_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+eprstmt_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='eprstmt-dev',
+        path='json',
+        data_files='./data/FewCLUE/eprstmt/dev_few_all.json',
+        split='train',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg),
+    dict(
+        type=HFDataset,
+        abbr='eprstmt-test',
+        path='json',
+        data_files='./data/FewCLUE/eprstmt/test_public.json',
+        split='train',
+        reader_cfg=eprstmt_reader_cfg,
+        infer_cfg=eprstmt_infer_cfg,
+        eval_cfg=eprstmt_eval_cfg)
+]

opencompass/configs/datasets/FewCLUE_ocnli_fc/FewCLUE_ocnli_fc_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_ocnli_fc_gen_f97a97 import ocnli_fc_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_ocnli_fc/FewCLUE_ocnli_fc_gen_f97a97.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import CMNLIDatasetV2
+from opencompass.utils.text_postprocessors import first_capital_postprocess
+
+ocnli_fc_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+ocnli_fc_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role='HUMAN',
+                prompt=
+                '阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}\nA. 对\nB. 错\nC. 可能\n请从“A”，“B”，“C”中进行选择。\n答：'
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+ocnli_fc_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role='BOT',
+    pred_postprocessor=dict(type=first_capital_postprocess),
+)
+
+ocnli_fc_datasets = [
+    dict(
+        abbr='ocnli_fc-dev',
+        type=CMNLIDatasetV2,  # ocnli_fc share the same format with cmnli
+        path='./data/FewCLUE/ocnli/dev_few_all.json',
+        local_mode=True,
+        reader_cfg=ocnli_fc_reader_cfg,
+        infer_cfg=ocnli_fc_infer_cfg,
+        eval_cfg=ocnli_fc_eval_cfg,
+    ),
+    dict(
+        abbr='ocnli_fc-test',
+        type=CMNLIDatasetV2,  # ocnli_fc share the same format with cmnli
+        path='./data/FewCLUE/ocnli/test_public.json',
+        local_mode=True,
+        reader_cfg=ocnli_fc_reader_cfg,
+        infer_cfg=ocnli_fc_infer_cfg,
+        eval_cfg=ocnli_fc_eval_cfg,
+    ),
+]

opencompass/configs/datasets/FewCLUE_ocnli_fc/FewCLUE_ocnli_fc_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_ocnli_fc_ppl_c08300 import ocnli_fc_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_ocnli_fc/FewCLUE_ocnli_fc_ppl_9e8b3d.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+ocnli_fc_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+ocnli_fc_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'contradiction':
+            dict(round=[
+                dict(
+                    role='HUMAN',
+                    prompt='阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}？'),
+                dict(role='BOT', prompt='错')
+            ]),
+            'entailment':
+            dict(round=[
+                dict(
+                    role='HUMAN',
+                    prompt='阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}？'),
+                dict(role='BOT', prompt='对')
+            ]),
+            'neutral':
+            dict(round=[
+                dict(
+                    role='HUMAN', prompt='如果{sentence1}为真，那么{sentence2}也为真吗？'),
+                dict(role='BOT', prompt='可能')
+            ]),
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+ocnli_fc_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+ocnli_fc_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='ocnli_fc-dev',
+        path='json',
+        split='train',
+        data_files='./data/FewCLUE/ocnli/dev_few_all.json',
+        reader_cfg=ocnli_fc_reader_cfg,
+        infer_cfg=ocnli_fc_infer_cfg,
+        eval_cfg=ocnli_fc_eval_cfg),
+    dict(
+        type=HFDataset,
+        abbr='ocnli_fc-test',
+        path='json',
+        split='train',
+        data_files='./data/FewCLUE/ocnli/test_public.json',
+        reader_cfg=ocnli_fc_reader_cfg,
+        infer_cfg=ocnli_fc_infer_cfg,
+        eval_cfg=ocnli_fc_eval_cfg)
+]

opencompass/configs/datasets/FewCLUE_ocnli_fc/FewCLUE_ocnli_fc_ppl_c08300.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+ocnli_fc_reader_cfg = dict(
+    input_columns=['sentence1', 'sentence2'],
+    output_column='label',
+    test_split='train')
+
+ocnli_fc_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            'contradiction':
+            '阅读文章：{sentence1}\n根据上文，回答如下问题： {sentence2}？\n答：错',
+            'entailment': '阅读文章：{sentence1}\n根据上文，回答如下问题： {sentence2}？\n答：对',
+            'neutral': '如果{sentence1}为真，那么{sentence2}也为真吗?可能'
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+ocnli_fc_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+ocnli_fc_datasets = [
+    dict(
+        type=HFDataset,
+        abbr='ocnli_fc-dev',
+        path='json',
+        split='train',
+        data_files='./data/FewCLUE/ocnli/dev_few_all.json',
+        reader_cfg=ocnli_fc_reader_cfg,
+        infer_cfg=ocnli_fc_infer_cfg,
+        eval_cfg=ocnli_fc_eval_cfg),
+    dict(
+        type=HFDataset,
+        abbr='ocnli_fc-test',
+        path='json',
+        split='train',
+        data_files='./data/FewCLUE/ocnli/test_public.json',
+        reader_cfg=ocnli_fc_reader_cfg,
+        infer_cfg=ocnli_fc_infer_cfg,
+        eval_cfg=ocnli_fc_eval_cfg)
+]

opencompass/configs/datasets/FewCLUE_tnews/FewCLUE_tnews_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_tnews_gen_b90e4a import tnews_datasets  # noqa: F401, F403

opencompass/configs/datasets/FewCLUE_tnews/FewCLUE_tnews_gen_b90e4a.py

+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import ZeroRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import TNewsDatasetV2
+from opencompass.utils.text_postprocessors import first_capital_postprocess
+
+tnews_reader_cfg = dict(
+    input_columns='sentence',
+    output_column='label_desc2',
+)
+
+tnews_labels = [
+    '农业新闻',  # news_agriculture
+    '旅游新闻',  # news_travel
+    '游戏新闻',  # news_game
+    '科技类别公司新闻',  # news_tech
+    '体育类别新闻',  # news_sports
+    '初升高教育新闻',  # news_edu
+    '娱乐圈新闻',  # news_entertainment
+    '投资资讯',  # news_finance
+    '军事类别常识',  # news_military
+    '车辆新闻',  # news_car
+    '楼市新闻',  # news_house
+    '环球不含中国类别新闻',  # news_world
+    '书籍文化历史类别新闻',  # news_culture
+    '故事类别新闻',  # news_story
+    '股票市场类别新闻',  # news_stock
+]
+_tnews_options_list_str = '\n'.join(f'{chr(ord("A") + i)}. {tnews_labels[i]}'
+                                    for i in range(len(tnews_labels)))
+_tnews_options_range_str = '，'.join(f'“{chr(ord("A") + i)}”'
+                                    for i in range(len(tnews_labels)))
+
+tnews_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role='HUMAN',
+                prompt=
+                f'{{sentence}}\n请判断上述内容属于什么新闻？\n{_tnews_options_list_str}\n请从{_tnews_options_range_str}中进行选择。\n答：',
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+tnews_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role='BOT',
+    pred_postprocessor=dict(type=first_capital_postprocess),
+)
+
+tnews_datasets = [
+    dict(
+        abbr='tnews-dev',
+        type=TNewsDatasetV2,
+        path='./data/FewCLUE/tnews/dev_few_all.json',
+        reader_cfg=tnews_reader_cfg,
+        infer_cfg=tnews_infer_cfg,
+        eval_cfg=tnews_eval_cfg,
+    ),
+    dict(
+        abbr='tnews-test',
+        type=TNewsDatasetV2,
+        path='./data/FewCLUE/tnews/test_public.json',
+        reader_cfg=tnews_reader_cfg,
+        infer_cfg=tnews_infer_cfg,
+        eval_cfg=tnews_eval_cfg,
+    ),
+]
+
+del _tnews_options_list_str, _tnews_options_range_str

opencompass/configs/datasets/FewCLUE_tnews/FewCLUE_tnews_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .FewCLUE_tnews_ppl_d10e8a import tnews_datasets  # noqa: F401, F403