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44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
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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.openicl.icl_evaluator import EMEvaluator, RougeEvaluator, SquadEvaluator, AccEvaluator
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from opencompass.datasets import LEvalGSM100Dataset
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from opencompass.utils.text_postprocessors import first_capital_postprocess, first_capital_postprocess_multi
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from opencompass.registry import TEXT_POSTPROCESSORS
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from opencompass.datasets import gsm100_dataset_postprocess, gsm100_postprocess
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LEval_gsm100_reader_cfg = dict(
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input_columns=['context', 'question'],
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output_column='answer',
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train_split='test',
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test_split='test'
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)
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LEval_gsm100_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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round=[
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dict(role='HUMAN', prompt='{question}\n'),
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], )),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer, max_out_len=512)
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)
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LEval_gsm100_eval_cfg = dict(evaluator=dict(type=AccEvaluator),
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pred_postprocessor=dict(type=gsm100_postprocess),
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dataset_postprocessor=dict(type=gsm100_dataset_postprocess)
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)
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LEval_gsm100_datasets = [
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dict(
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type=LEvalGSM100Dataset,
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abbr='LEval_gsm100',
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path='L4NLP/LEval',
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name='gsm100',
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reader_cfg=LEval_gsm100_reader_cfg,
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infer_cfg=LEval_gsm100_infer_cfg,
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eval_cfg=LEval_gsm100_eval_cfg)
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]
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