[SIG] add GLUE_MRPC dataset (#440)

configs/datasets/GLUE_MRPC/GLUE_MRPC_ppl.py

@@ -0,0 +1,4 @@
+from mmengine.config import read_base
+
+with read_base():
+    from .GLUE_MRPC_ppl_96564c import MRPC_datasets  # noqa: F401, F403

configs/datasets/GLUE_MRPC/GLUE_MRPC_ppl_96564c.py

@@ -0,0 +1,51 @@
+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import FixKRetriever
+from opencompass.openicl.icl_inferencer import PPLInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import HFDataset
+
+
+_hint = "The following are semantic matching questions. \n" \
+    "Please determine whether the following two sentences are semantically equivalent: " \
+    "0 means not equivalent, 1 means equivalent.\n"
+MRPC_infer_cfg = dict(
+    ice_template=dict(
+        type=PromptTemplate,
+        template="Sentence one: {sentence1}\nSentence two: {sentence2}\nResult: {label}",
+    ),
+    prompt_template=dict(
+        type=PromptTemplate,
+        template={
+            answer:
+            f"{_hint}</E>Sentence one: {{sentence1}}\nSentence two: {{sentence2}}\nResult: {answer}"
+            for answer in [0, 1]
+        },
+        ice_token='</E>',
+    ),
+    retriever=dict(type=FixKRetriever),
+    inferencer=dict(type=PPLInferencer, fix_id_list=[0, 1, 2, 3, 4]))
+
+MRPC_eval_cfg = dict(evaluator=dict(type=AccEvaluator), )
+
+
+MRPC_datasets = []
+for _split in ["validation", "test"]:
+
+    MRPC_reader_cfg = dict(
+        input_columns=['sentence1', 'sentence2'],
+        output_column='label',
+        train_split="train",
+        test_split=_split
+    )
+
+    MRPC_datasets.append(
+        dict(
+            abbr=f'MRPC-{_split}',
+            type=HFDataset,
+            path='glue',
+            name='mrpc',
+            reader_cfg=MRPC_reader_cfg,
+            infer_cfg=MRPC_infer_cfg,
+            eval_cfg=MRPC_eval_cfg
+        )
+    )