from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import WSCDataset

WSC_reader_cfg = dict(
    input_columns=["span1", "span2", "text", "new_text"],
    output_column="answer",
)

WSC_infer_cfg = dict(
    prompt_template=dict(
        type=PromptTemplate,
        template={
            0: dict(round=[
                dict(role="HUMAN", prompt="{text}"),
            ]),
            1: dict(round=[
                dict(role="HUMAN", prompt="{new_text}"),
            ]),
        },
    ),
    retriever=dict(type=ZeroRetriever),
    inferencer=dict(type=PPLInferencer),
)

WSC_eval_cfg = dict(evaluator=dict(type=AccEvaluator))

WSC_datasets = [
    dict(
        type=WSCDataset,
        path="json",
        abbr="WSC",
        data_files="./data/SuperGLUE/WSC/val.jsonl",
        split="train",
        reader_cfg=WSC_reader_cfg,
        infer_cfg=WSC_infer_cfg,
        eval_cfg=WSC_eval_cfg,
    )
]