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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 PPLInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import TNewsDataset
tnews_reader_cfg = dict(input_columns='sentence', output_column='label_desc2')
tnews_labels = [
'农业新闻', '旅游新闻', '游戏新闻', '科技类别公司新闻', '体育类别新闻', '初升高教育新闻', '娱乐圈新闻', '投资资讯',
'军事类别常识', '车辆新闻', '楼市新闻', '环球不含中国类别新闻', '书籍文化历史类别新闻', '故事类别新闻', '股票市场类别新闻'
]
tnews_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template={
lb: dict(round=[
dict(role='HUMAN', prompt='以下内容属于什么新闻：{sentence}。'),
dict(role='BOT', prompt=lb)
])
for lb in tnews_labels
}),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=PPLInferencer))
tnews_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
tnews_datasets = [
dict(
type=TNewsDataset,
path='json',
abbr='tnews-dev',
data_files='./data/FewCLUE/tnews/dev_few_all.json',
split='train',
reader_cfg=tnews_reader_cfg,
infer_cfg=tnews_infer_cfg,
eval_cfg=tnews_eval_cfg),
dict(
type=TNewsDataset,
path='json',
abbr='tnews-test',
data_files='./data/FewCLUE/tnews/test_public.json',
split='train',
reader_cfg=tnews_reader_cfg,
infer_cfg=tnews_infer_cfg,
eval_cfg=tnews_eval_cfg)
]
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