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* [Feature] Support 360API and FixKRetriever for CSQA dataset * Update API * Update API * [Feature] Support 360API and FixKRetriever for CSQA dataset * Update API * Update API * rm mathbench * fix_lint * Update opencompass/models/bytedance_api.py Co-authored-by: Hubert <42952108+yingfhu@users.noreply.github.com> * update * update * update --------- Co-authored-by: Hubert <42952108+yingfhu@users.noreply.github.com>
43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import FixKRetriever
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from opencompass.openicl.icl_inferencer import PPLInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import commonsenseqaDataset
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commonsenseqa_reader_cfg = dict(
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input_columns=['question', 'A', 'B', 'C', 'D', 'E'],
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output_column='answerKey',
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test_split='validation')
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_ice_template = dict(
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type=PromptTemplate,
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template={
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ans: dict(
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begin='</E>',
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round=[
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dict(role="HUMAN", prompt="Question: {question}\nAnswer: "),
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dict(role="BOT", prompt=ans_token),
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])
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for ans, ans_token in [["A", "{A}"], ["B", "{B}"],
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["C", "{C}"], ["D", "{D}"],
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["E", "{E}"]]
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},
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ice_token='</E>')
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commonsenseqa_infer_cfg = dict(
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ice_template=_ice_template,
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retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4, 5, 6, 7]),
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inferencer=dict(type=PPLInferencer))
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commonsenseqa_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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commonsenseqa_datasets = [
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dict(
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abbr='commonsense_qa',
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type=commonsenseqaDataset,
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path='./data/commonsenseqa',
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reader_cfg=commonsenseqa_reader_cfg,
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infer_cfg=commonsenseqa_infer_cfg,
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eval_cfg=commonsenseqa_eval_cfg)
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]
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