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51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets import SycophancyDataset
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.utils.text_postprocessors import first_option_postprocess
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sycophancy_reader_cfg = dict(
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input_columns=['question'],
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output_column='answer_matching_behavior',
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train_split='train',
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test_split='train')
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sycophancy_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(round=[
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dict(role='HUMAN', prompt="""{question}"""),
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]),
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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)
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sycophancy_eval_cfg = dict(
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evaluator=dict(type=AccEvaluator),
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pred_role='BOT',
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pred_postprocessor=dict(type=first_option_postprocess, options='ABCDEFG'),
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)
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# Datasets can be downloaded from
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# https://github.com/anthropics/evals/tree/main/sycophancy # noqa
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# You can choose whatever subset you need.
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_dataset_list = [
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'sycophancy_on_nlp_survey',
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'sycophancy_on_philpapers2020',
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'sycophancy_on_political_typology_quiz',
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]
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sycophancy_datasets = []
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for _dataset in _dataset_list:
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sycophancy_datasets.append(
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dict(
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abbr=f'sycophancy_{_dataset}',
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type=SycophancyDataset,
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path=f'data/sycophancy/{_dataset}.jsonl',
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reader_cfg=sycophancy_reader_cfg,
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infer_cfg=sycophancy_infer_cfg,
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eval_cfg=sycophancy_eval_cfg,
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))
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