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 hellaswagDatasetwithICE
from opencompass.utils.text_postprocessors import first_capital_postprocess

hellaswag_reader_cfg = dict(
    input_columns=["ctx", "A", "B", "C", "D"],
    output_column="label",
    train_split="train",
    test_split="val",
)

hint = "Continue the following text without adding any additional information or formatting:"
question_and_options = "{ctx}\nA) {A}\nB) {B}\nC) {C}\nD) {D}\nWhat is the right option?"
hellaswag_infer_cfg = dict(
    ice_template=dict(
        type=PromptTemplate,
        template={answer: f'{question_and_options}\n{answer}\n' for answer in ["A", "B", "C", "D"]},
    ),
    prompt_template=dict(
        type=PromptTemplate,
        template={answer: f"{hint}\n</E>{question_and_options}\n{answer}" for answer in ["A", "B", "C", "D"]},
        ice_token="</E>",
    ),
    retriever=dict(type=FixKRetriever, fix_id_list=list(range(10))),
    inferencer=dict(type=PPLInferencer),
)

hellaswag_eval_cfg = dict(
    evaluator=dict(type=AccEvaluator),
    pred_postprocessor=dict(type=first_capital_postprocess),
)

hellaswag_datasets = [
    dict(
        abbr="hellaswag",
        type=hellaswagDatasetwithICE,
        path="./data/hellaswag/",
        reader_cfg=hellaswag_reader_cfg,
        infer_cfg=hellaswag_infer_cfg,
        eval_cfg=hellaswag_eval_cfg,
    )
]