Add Release Contraibution

.pre-commit-config.yaml

+exclude: |
+    (?x)^(
+      tests/data/|
+      opencompass/models/internal/|
+      opencompass/utils/internal/|
+      configs/
+    )
+repos:
+  - repo: https://github.com/PyCQA/flake8
+    rev: 5.0.4
+    hooks:
+      - id: flake8
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.11.5
+    hooks:
+      - id: isort
+  - repo: https://github.com/pre-commit/mirrors-yapf
+    rev: v0.32.0
+    hooks:
+      - id: yapf
+  - repo: https://github.com/codespell-project/codespell
+    rev: v2.2.1
+    hooks:
+      - id: codespell
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.3.0
+    hooks:
+      - id: trailing-whitespace
+        exclude: |
+            (?x)^(
+              dicts/|
+              projects/.*?/dicts/
+            )
+      - id: check-yaml
+      - id: end-of-file-fixer
+        exclude: |
+            (?x)^(
+              dicts/|
+              projects/.*?/dicts/
+            )
+      - id: requirements-txt-fixer
+      - id: double-quote-string-fixer
+      - id: check-merge-conflict
+      - id: fix-encoding-pragma
+        args: ["--remove"]
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+      - id: mixed-line-ending
+        args: ["--fix=lf"]
+  - repo: https://github.com/executablebooks/mdformat
+    rev: 0.7.9
+    hooks:
+      - id: mdformat
+        args: ["--number", "--table-width", "200"]
+        additional_dependencies:
+          - mdformat-openmmlab
+          - mdformat_frontmatter
+          - linkify-it-py
+  - repo: https://github.com/myint/docformatter
+    rev: v1.3.1
+    hooks:
+      - id: docformatter
+        args: ["--in-place", "--wrap-descriptions", "79"]
+  # - repo: https://github.com/open-mmlab/pre-commit-hooks
+  #   rev: v0.2.0  # Use the ref you want to point at
+  #   hooks:
+  #     - id: check-algo-readme
+      # - id: check-copyright
+      #   args: ["mmocr", "tests", "tools"]  # these directories will be checked

configs/datasets/ARC_e/ARC_e_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .ARC_e_ppl_f86898 import ARC_e_datasets  # noqa: F401, F403

configs/datasets/CLUE_C3/CLUE_C3_ppl_588820.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 C3Dataset
+
+C3_reader_cfg = dict(
+    input_columns=[
+        'question', 'content', 'choice0', 'choice1', 'choice2', 'choice3',
+        'choices'
+    ],
+    output_column='label')
+
+C3_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            i: dict(round=[
+                dict(role="HUMAN", prompt="文章：{content}\n问题：{question}"),
+                dict(role="BOT", prompt=f"答案：{{choice{i}}}")
+            ])
+            for i in range(4)
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+C3_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+C3_datasets = [
+    dict(
+        type=C3Dataset,
+        abbr='C3',
+        path='./data/CLUE/C3/dev_0.json',
+        reader_cfg=C3_reader_cfg,
+        infer_cfg=C3_infer_cfg,
+        eval_cfg=C3_eval_cfg)
+]

configs/datasets/CLUE_CMRC/CLUE_CMRC_gen_72a8d5.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 EMEvaluator
+from opencompass.datasets import CMRCDataset
+
+CMRC_reader_cfg = dict(
+    input_columns=['question', 'context'], output_column='answers')
+
+CMRC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt="文章：{context}\n根据上文，回答如下问题：\n{question}\n答："),
+        ])),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer))
+
+CMRC_eval_cfg = dict(
+    evaluator=dict(type=EMEvaluator),
+    pred_role="BOT",
+)
+
+CMRC_datasets = [
+    dict(
+        type=CMRCDataset,
+        abbr='CMRC_dev',
+        path='./data/CLUE/CMRC/dev.json',
+        reader_cfg=CMRC_reader_cfg,
+        infer_cfg=CMRC_infer_cfg,
+        eval_cfg=CMRC_eval_cfg),
+]

configs/datasets/CLUE_CMRC/CLUE_CMRC_gen_d7096f.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 EMEvaluator
+from opencompass.datasets import CMRCDataset
+
+CMRC_reader_cfg = dict(
+    input_columns=['question', 'context'], output_column='answers')
+
+CMRC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(role="HUMAN", prompt="文章：{context}\n根据上文，回答如下问题：{question}"),
+            dict(role="BOT", prompt="答："),
+        ])),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer))
+
+CMRC_eval_cfg = dict(
+    evaluator=dict(type=EMEvaluator),
+    pred_role="BOT",
+)
+
+CMRC_datasets = [
+    dict(
+        type=CMRCDataset,
+        abbr='CMRC_dev',
+        path='./data/CLUE/CMRC/dev.json',
+        reader_cfg=CMRC_reader_cfg,
+        infer_cfg=CMRC_infer_cfg,
+        eval_cfg=CMRC_eval_cfg),
+]

configs/datasets/CLUE_DRCD/CLUE_DRCD_gen_03b96b.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 EMEvaluator
+from opencompass.datasets import DRCDDataset
+
+DRCD_reader_cfg = dict(
+    input_columns=['question', 'context'], output_column='answers')
+
+DRCD_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt="文章：{context}\n根据上文，回答如下问题：\n{question}\n答："),
+        ])),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer))
+
+DRCD_eval_cfg = dict(
+    evaluator=dict(type=EMEvaluator),
+    pred_role="BOT",
+)
+
+DRCD_datasets = [
+    dict(
+        type=DRCDDataset,
+        abbr='DRCD_dev',
+        path='./data/CLUE/DRCD/dev.json',
+        reader_cfg=DRCD_reader_cfg,
+        infer_cfg=DRCD_infer_cfg,
+        eval_cfg=DRCD_eval_cfg),
+]

configs/datasets/FewCLUE_bustm/FewCLUE_bustm_gen_305431.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 AFQMCDataset_V2
+
+bustm_reader_cfg = dict(
+    input_columns=["sentence1", "sentence2"],
+    output_column="label",
+    test_split="train")
+
+bustm_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                "语句一：“{sentence1}”\n语句二：“{sentence2}”\n请判断语句一和语句二说的是否是一个意思？\nA. 无关\nB. 相关\n请从“A”，“B”中进行选择。\n答：",
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+bustm_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+bustm_datasets = [
+    dict(
+        abbr="bustm-dev",
+        type=AFQMCDataset_V2,  # bustm share the same format with AFQMC
+        path="./data/FewCLUE/bustm/dev_few_all.json",
+        reader_cfg=bustm_reader_cfg,
+        infer_cfg=bustm_infer_cfg,
+        eval_cfg=bustm_eval_cfg,
+    ),
+    dict(
+        abbr="bustm-test",
+        type=AFQMCDataset_V2,  # bustm share the same format with AFQMC
+        path="./data/FewCLUE/bustm/test_public.json",
+        reader_cfg=bustm_reader_cfg,
+        infer_cfg=bustm_infer_cfg,
+        eval_cfg=bustm_eval_cfg,
+    ),
+]

configs/datasets/FewCLUE_chid/FewCLUE_chid_ppl_b6cd88.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 CHIDDataset
+
+chid_reader_cfg = dict(
+    input_columns=[f'content{i}' for i in range(7)], output_column='answer')
+
+chid_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            i: dict(
+                round=[
+                    dict(role="HUMAN", prompt=f"以下句子是否通顺？\n{{content{i}}}"),
+                    dict(role="BOT", prompt="这个句子是通顺的。"),
+                ], )
+            for i in range(7)
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+chid_eval_cfg = dict(evaluator=dict(type=AccEvaluator), pred_role="BOT")
+
+chid_datasets = [
+    dict(
+        type=CHIDDataset,
+        path='json',
+        abbr='chid-dev',
+        data_files='./data/FewCLUE/chid/dev_few_all.json',
+        split='train',
+        reader_cfg=chid_reader_cfg,
+        infer_cfg=chid_infer_cfg,
+        eval_cfg=chid_eval_cfg),
+    dict(
+        type=CHIDDataset,
+        path='json',
+        abbr='chid-test',
+        data_files='./data/FewCLUE/chid/test_public.json',
+        split='train',
+        reader_cfg=chid_reader_cfg,
+        infer_cfg=chid_infer_cfg,
+        eval_cfg=chid_eval_cfg),
+]

configs/datasets/FewCLUE_cluewsc/FewCLUE_cluewsc_ppl_fc45f0.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}\nHere, is the pronoun \"{span2}\" used to mean \"{span1}\"?"
+                ),
+                dict(role="BOT", prompt="No.")
+            ]),
+            1:
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "{text}\nHere, is the pronoun \"{span2}\" used to mean \"{span1}\"?"
+                ),
+                dict(role="BOT", prompt="Yes.")
+            ]),
+        }),
+    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),
+]

configs/datasets/FewCLUE_tnews/FewCLUE_tnews_ppl_784b9e.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 TNewsDataset
+
+tnews_reader_cfg = dict(input_columns='sentence', output_column='label_desc2')
+
+tnews_labels = [
+    '农业新闻', '旅游新闻', '游戏新闻', '科技类别公司新闻', '体育类别新闻', '初升高教育新闻', '娱乐圈新闻', '投资资讯',
+    '军事类别常识', '车辆新闻', '楼市新闻', '环球不含中国类别新闻', '书籍文化历史类别新闻', '故事类别新闻', '股票市场类别新闻'
+]
+
+tnews_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            lb: dict(round=[
+                dict(role='HUMAN', prompt='{sentence}\n上述内容属于什么新闻？'),
+                dict(role='BOT', prompt=lb)
+            ])
+            for lb in tnews_labels
+        }),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer))
+
+tnews_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+tnews_datasets = [
+    dict(
+        type=TNewsDataset,
+        path='json',
+        abbr='tnews-dev',
+        data_files='./data/FewCLUE/tnews/dev_few_all.json',
+        split='train',
+        reader_cfg=tnews_reader_cfg,
+        infer_cfg=tnews_infer_cfg,
+        eval_cfg=tnews_eval_cfg),
+    dict(
+        type=TNewsDataset,
+        path='json',
+        abbr='tnews-test',
+        data_files='./data/FewCLUE/tnews/test_public.json',
+        split='train',
+        reader_cfg=tnews_reader_cfg,
+        infer_cfg=tnews_infer_cfg,
+        eval_cfg=tnews_eval_cfg)
+]

configs/datasets/GaokaoBench/GaokaoBench_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .GaokaoBench_gen_aed980 import GaokaoBench_datasets  # noqa: F401, F403

configs/datasets/SuperGLUE_AX_g/SuperGLUE_AX_g_gen_7a5dee.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 AXDataset_V2
+
+AX_g_reader_cfg = dict(
+    input_columns=["hypothesis", "premise"],
+    output_column="label",
+)
+
+AX_g_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                "{premise}\n{hypothesis}\nIs the sentence below entailed by the sentence above?\nA. Yes\nB. No\nAnswer:"
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+AX_g_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+AX_g_datasets = [
+    dict(
+        abbr="AX_g",
+        type=AXDataset_V2,
+        path="./data/SuperGLUE/AX-g/AX-g.jsonl",
+        reader_cfg=AX_g_reader_cfg,
+        infer_cfg=AX_g_infer_cfg,
+        eval_cfg=AX_g_eval_cfg,
+    )
+]

configs/datasets/SuperGLUE_AX_g/SuperGLUE_AX_g_ppl_8d9bf9.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
+
+AX_g_reader_cfg = dict(
+    input_columns=["hypothesis", "premise"],
+    output_column="label",
+    test_split="train")
+
+AX_g_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            "entailment":
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "{premise}\n{hypothesis}\nIs the sentence below entailed by the sentence above?"
+                ),
+                dict(role="BOT", prompt="Yes"),
+            ]),
+            "not_entailment":
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "{premise}\n{hypothesis}\nIs the sentence below entailed by the sentence above?"
+                ),
+                dict(role="BOT", prompt="No"),
+            ])
+        },
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer),
+)
+
+AX_g_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+AX_g_datasets = [
+    dict(
+        type=HFDataset,
+        abbr="AX_g",
+        path="json",
+        data_files="./data/SuperGLUE/AX-g/AX-g.jsonl",
+        split="train",
+        reader_cfg=AX_g_reader_cfg,
+        infer_cfg=AX_g_infer_cfg,
+        eval_cfg=AX_g_eval_cfg,
+    )
+]

configs/datasets/SuperGLUE_BoolQ/SuperGLUE_BoolQ_ppl.py

+from mmengine.config import read_base
+
+with read_base():
+    from .SuperGLUE_BoolQ_ppl_f80fb0 import BoolQ_datasets  # noqa: F401, F403

configs/datasets/SuperGLUE_CB/SuperGLUE_CB_gen.py

+from mmengine.config import read_base
+
+with read_base():
+    from .SuperGLUE_CB_gen_bb97e1 import CB_datasets  # noqa: F401, F403

configs/datasets/SuperGLUE_COPA/SuperGLUE_COPA_gen_6d5e67.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 COPADataset_V2
+
+COPA_reader_cfg = dict(
+    input_columns=["question", "premise", "choice1", "choice2"],
+    output_column="label",
+)
+
+COPA_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(
+            round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "{premise}\nQuestion: Which may be the {question}?\nA. {choice1}\nB. {choice2}\nAnswer:"
+                ),
+            ], ),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+COPA_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+COPA_datasets = [
+    dict(
+        abbr="COPA",
+        type=COPADataset_V2,
+        path="./data/SuperGLUE/COPA/val.jsonl",
+        reader_cfg=COPA_reader_cfg,
+        infer_cfg=COPA_infer_cfg,
+        eval_cfg=COPA_eval_cfg,
+    )
+]

configs/datasets/SuperGLUE_MultiRC/SuperGLUE_MultiRC_gen_26c9dc.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 MultiRCDataset_V2
+
+MultiRC_reader_cfg = dict(
+    input_columns=["question", "text", "answer"],
+    output_column="label",
+)
+
+MultiRC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                "{text}\nQuestion: {question}\nAnswer: {answer}\nIs it true?\nA. Yes\nB. No\nAnswer:"
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+MultiRC_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+MultiRC_datasets = [
+    dict(
+        abbr="MultiRC",
+        type=MultiRCDataset_V2,
+        path="./data/SuperGLUE/MultiRC/val.jsonl",
+        reader_cfg=MultiRC_reader_cfg,
+        infer_cfg=MultiRC_infer_cfg,
+        eval_cfg=MultiRC_eval_cfg,
+    )
+]

configs/datasets/SuperGLUE_WiC/SuperGLUE_WiC_gen_c39367.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 WiCDataset_V2
+
+WiC_reader_cfg = dict(
+    input_columns=[
+        "word",
+        "sentence1",
+        "sentence2",
+    ],
+    output_column="label",
+)
+
+WiC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template=dict(round=[
+            dict(
+                role="HUMAN",
+                prompt=
+                "Sentence 1: {sentence1}\nSentence 2: {sentence2}\nAre '{word}' in the above two sentenses the same?\nA. Yes\nB. No\nAnswer:"
+            ),
+        ]),
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=GenInferencer),
+)
+
+WiC_eval_cfg = dict(
+    evaluator=dict(type=AccEvaluator),
+    pred_role="BOT",
+    pred_postprocessor=dict(type="first-capital"),
+)
+
+WiC_datasets = [
+    dict(
+        abbr="WiC",
+        type=WiCDataset_V2,
+        path="./data/SuperGLUE/WiC/val.jsonl",
+        reader_cfg=WiC_reader_cfg,
+        infer_cfg=WiC_infer_cfg,
+        eval_cfg=WiC_eval_cfg,
+    )
+]

configs/datasets/SuperGLUE_WiC/SuperGLUE_WiC_ppl_4118db.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 WiCDataset
+
+WiC_reader_cfg = dict(
+    input_columns=[
+        "word",
+        "sentence1",
+        "sentence2",
+    ],
+    output_column="answer",
+    test_split="train")
+
+WiC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0:
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "Sentence 1: {sentence1}\nSentence 2: {sentence2}\n'{word}' in the above two sentenses are different."
+                ),
+            ]),
+            1:
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    "Sentence 1: {sentence1}\nSentence 2: {sentence2}\n'{word}' in the above two sentenses are the same."
+                ),
+            ]),
+        },
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer),
+)
+
+WiC_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+WiC_datasets = [
+    dict(
+        type=WiCDataset,
+        abbr="WiC",
+        path="json",
+        data_files="./data/SuperGLUE/WiC/val.jsonl",
+        split="train",
+        reader_cfg=WiC_reader_cfg,
+        infer_cfg=WiC_infer_cfg,
+        eval_cfg=WiC_eval_cfg,
+    )
+]

configs/datasets/SuperGLUE_WiC/SuperGLUE_WiC_ppl_d316eb.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 WiCDataset
+
+WiC_reader_cfg = dict(
+    input_columns=[
+        "word",
+        "sentence1",
+        "sentence2",
+    ],
+    output_column="answer",
+    test_split="train")
+
+WiC_infer_cfg = dict(
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            0:
+            dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt="{word} in {sentence1} and {sentence2} is different."),
+            ]),
+            1:
+            dict(round=[
+                dict(role="HUMAN", prompt="{word} in {sentence1} and {sentence2} is same."),
+            ]),
+        },
+    ),
+    retriever=dict(type=ZeroRetriever),
+    inferencer=dict(type=PPLInferencer),
+)
+
+WiC_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
+
+WiC_datasets = [
+    dict(
+        type=WiCDataset,
+        abbr="WiC",
+        path="json",
+        data_files="./data/SuperGLUE/WiC/val.jsonl",
+        split="train",
+        reader_cfg=WiC_reader_cfg,
+        infer_cfg=WiC_infer_cfg,
+        eval_cfg=WiC_eval_cfg,
+    )
+]