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51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
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from mmengine.config import read_base
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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.OpenHuEval.HuMatchingFIB import HuMatchingFIBDataset, HuMatchingFIBEvaluator
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with read_base():
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from .HuMatchingFIB_setting import INSTRUCTIONS, DATASET_PATH
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ALL_LANGUAGES = ['hu']
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PROMPT_VERSION = INSTRUCTIONS['version']
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FIB1_reader_cfg = dict(input_columns=['question', 'subject'],
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output_column='reference')
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FIB1_datasets = []
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for lan in ALL_LANGUAGES:
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instruction = INSTRUCTIONS[lan]
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FIB1_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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begin='</E>',
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round=[
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dict(
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role='HUMAN',
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prompt=instruction
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),
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],
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),
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ice_token='</E>',
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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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FIB1_eval_cfg = dict(evaluator=dict(type=HuMatchingFIBEvaluator))
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FIB1_datasets.append(
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dict(
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abbr=f'nkp_FIB1_humanities-{lan}-1shot-{PROMPT_VERSION}',
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type=HuMatchingFIBDataset,
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path=DATASET_PATH,
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lan=lan,
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reader_cfg=FIB1_reader_cfg,
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infer_cfg=FIB1_infer_cfg,
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eval_cfg=FIB1_eval_cfg,
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)
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)
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