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from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import CMBDataset
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.utils.text_postprocessors import multiple_select_postprocess
cmb_datasets = []
for split in ["val", "test"]:
cmb_reader_cfg = dict(
input_columns=["exam_type", "exam_class", "question_type", "question", "option_str"],
output_column="answer",
train_split=split,
test_split=split,
)
cmb_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(
role="HUMAN",
prompt=f"以下是中国{{exam_type}}中{{exam_class}}考试的一道{{question_type}}，不需要做任何分析和解释，直接输出答案选项。\n{{question}}\n{{option_str}} \n 答案: ",
),
dict(role="BOT", prompt="{answer}"),
],
),
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=10),
)
cmb_eval_cfg = dict(
evaluator=dict(type=AccEvaluator),
pred_postprocessor=dict(type=multiple_select_postprocess),
)
cmb_datasets.append(
dict(
abbr="cmb" if split == "val" else "cmb_test",
type=CMBDataset,
path="./data/CMB/",
reader_cfg=cmb_reader_cfg,
infer_cfg=cmb_infer_cfg,
eval_cfg=cmb_eval_cfg,
)
)
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