from opencompass.openicl.icl_prompt_template import PromptTemplate from opencompass.openicl.icl_inferencer import GenInferencer from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.datasets import XiezhiDataset, XiezhiRetriever from opencompass.utils.text_postprocessors import first_capital_postprocess xiezhi_datasets = [] for split in ["spec_eng", "spec_chn", "inter_eng", "inter_chn"]: if 'chn' in split: q_hint, a_hint = "题目", "答案" else: q_hint, a_hint = "Question", "Answer" xiezhi_reader_cfg = dict( input_columns=["question", "A", "B", "C", "D", "labels"], output_column="answer", train_split="train", test_split='test', ) xiezhi_infer_cfg = dict( ice_template=dict( type=PromptTemplate, template=dict( begin="", round=[ dict(role="HUMAN", prompt=f"{q_hint}: {{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n{a_hint}: "), dict(role="BOT", prompt="{answer}"), ] ), ice_token="", ), retriever=dict(type=XiezhiRetriever, ice_num=3), inferencer=dict(type=GenInferencer), ) xiezhi_eval_cfg = dict(evaluator=dict(type=AccEvaluator), pred_role="BOT", pred_postprocessor=dict(type=first_capital_postprocess)) xiezhi_datasets.append( dict( type=XiezhiDataset, abbr=f"xiezhi-{split}", path="./data/xiezhi/", name="xiezhi_" + split, reader_cfg=xiezhi_reader_cfg, infer_cfg=xiezhi_infer_cfg, eval_cfg=xiezhi_eval_cfg, ))