from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import MDLRetriever
from opencompass.openicl.icl_inferencer import PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import commonsenseqaDataset

commonsenseqa_reader_cfg = dict(
    input_columns=['question', 'A', 'B', 'C', 'D', 'E'],
    output_column='answerKey',
    test_split='validation')

_ice_template = dict(
    type=PromptTemplate,
    template={
        ans: dict(
            begin='</E>',
            round=[
                dict(role='HUMAN', prompt='Question: {question}\nAnswer: '),
                dict(role='BOT', prompt=ans_token),
            ])
        for ans, ans_token in [['A', '{A}'], ['B', '{B}'],
                               ['C', '{C}'], ['D', '{D}'],
                               ['E', '{E}']]
    },
    ice_token='</E>')

commonsenseqa_infer_cfg = dict(
    ice_template=_ice_template,
    retriever=dict(
        type=MDLRetriever,
        ice_num=8,
        candidate_num=30,
        select_time=10,
        seed=1,
        batch_size=12,
        ice_template=_ice_template),
    inferencer=dict(type=PPLInferencer))

commonsenseqa_eval_cfg = dict(evaluator=dict(type=AccEvaluator))

commonsenseqa_datasets = [
    dict(
        abbr='commonsense_qa',
        type=commonsenseqaDataset,
        path='./data/commonsenseqa',
        reader_cfg=commonsenseqa_reader_cfg,
        infer_cfg=commonsenseqa_infer_cfg,
        eval_cfg=commonsenseqa_eval_cfg)
]
