update a new mmlu dataset config with more general post process

configs/datasets/mmlu/mmlu_gen_general_postprocess.py

@@ -0,0 +1,124 @@
+from opencompass.openicl.icl_prompt_template import PromptTemplate
+from opencompass.openicl.icl_retriever import FixKRetriever
+from opencompass.openicl.icl_inferencer import GenInferencer
+from opencompass.openicl.icl_evaluator import AccEvaluator
+from opencompass.datasets import MMLUDataset
+from opencompass.utils.text_postprocessors import general_post_capital_postprocess
+
+# None of the mmlu dataset in huggingface is correctly parsed, so we use our own dataset reader
+# Please download the dataset from https://people.eecs.berkeley.edu/~hendrycks/data.tar
+
+mmlu_reader_cfg = dict(
+    input_columns=["input", "A", "B", "C", "D"],
+    output_column="target",
+    train_split='dev')
+
+mmlu_all_sets = [
+    "college_biology",
+    "college_chemistry",
+    "college_computer_science",
+    "college_mathematics",
+    "college_physics",
+    "electrical_engineering",
+    "astronomy",
+    "anatomy",
+    "abstract_algebra",
+    "machine_learning",
+    "clinical_knowledge",
+    "global_facts",
+    "management",
+    "nutrition",
+    "marketing",
+    "professional_accounting",
+    "high_school_geography",
+    "international_law",
+    "moral_scenarios",
+    "computer_security",
+    "high_school_microeconomics",
+    "professional_law",
+    "medical_genetics",
+    "professional_psychology",
+    "jurisprudence",
+    "world_religions",
+    "philosophy",
+    "virology",
+    "high_school_chemistry",
+    "public_relations",
+    "high_school_macroeconomics",
+    "human_sexuality",
+    "elementary_mathematics",
+    "high_school_physics",
+    "high_school_computer_science",
+    "high_school_european_history",
+    "business_ethics",
+    "moral_disputes",
+    "high_school_statistics",
+    "miscellaneous",
+    "formal_logic",
+    "high_school_government_and_politics",
+    "prehistory",
+    "security_studies",
+    "high_school_biology",
+    "logical_fallacies",
+    "high_school_world_history",
+    "professional_medicine",
+    "high_school_mathematics",
+    "college_medicine",
+    "high_school_us_history",
+    "sociology",
+    "econometrics",
+    "high_school_psychology",
+    "human_aging",
+    "us_foreign_policy",
+    "conceptual_physics",
+]
+
+mmlu_datasets = []
+for _name in mmlu_all_sets:
+    _hint = f'There is a single choice question about {_name.replace("_", " ")}. Answer the question by replying A, B, C or D.'
+    mmlu_infer_cfg = dict(
+        ice_template=dict(
+            type=PromptTemplate,
+            template=dict(round=[
+                dict(
+                    role="HUMAN",
+                    prompt=
+                    f"{_hint}\nQuestion: {{input}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nAnswer: "
+                ),
+                dict(role="BOT", prompt="{target}\n")
+            ]),
+        ),
+        prompt_template=dict(
+            type=PromptTemplate,
+            template=dict(
+                begin="</E>",
+                round=[
+                    dict(
+                        role="HUMAN",
+                        prompt=
+                        f"{_hint}\nQuestion: {{input}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\nAnswer: "
+                    ),
+                ],
+            ),
+            ice_token="</E>",
+        ),
+        retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
+        inferencer=dict(type=GenInferencer),
+    )
+
+    mmlu_eval_cfg = dict(
+        evaluator=dict(type=AccEvaluator),
+        pred_postprocessor=dict(type=general_post_capital_postprocess))
+
+    mmlu_datasets.append(
+        dict(
+            abbr=f"lukaemon_mmlu_{_name}",
+            type=MMLUDataset,
+            path="./data/mmlu/",
+            name=_name,
+            reader_cfg=mmlu_reader_cfg,
+            infer_cfg=mmlu_infer_cfg,
+            eval_cfg=mmlu_eval_cfg,
+        ))
+
+del _name, _hint

opencompass/utils/text_postprocessors.py

@@ -56,6 +56,28 @@ def last_capital_postprocess(text: str) -> str:
             return t
     return ''
 
+@TEXT_POSTPROCESSORS.register_module('general_post_capital')
+def general_post_capital_postprocess(text: str) -> str:
+    patterns = [
+        "the answer is ([A-E])",
+        "the answer is([A-E])",
+        "the correct answer is ([A-E])",
+        "the correct answer is([A-E])",
+        "Answer: ([A-E])",
+        "Answer: \(([A-E])\)",
+        "Option \(([A-E])\)",
+        "Answer:([A-E])",
+        "Option ([A-E])",
+        "Opt ([A-E])"
+    ]
+    for pattern in patterns:
+        match = re.search(pattern,text,re.IGNORECASE)
+        if match:
+            return match.group(1)
+    match = re.findall("[A-D]", text)
+    if match:
+        return match[0]
+    return ""
 
 def first_option_postprocess(text: str, options: str, cushion=True) -> str:
     """Find first valid option for text."""