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* [Feature] Support import configs/models/summarizers from whl * Update LCBench configs * Update * Update * Update * Update * update * Update * Update * Update * Update * Update
51 lines
1.8 KiB
Python
51 lines
1.8 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 PPLInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import AnliDataset
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anli_datasets = []
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for _split in ['R1', 'R2', 'R3']:
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anli_reader_cfg = dict(
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input_columns=['context', 'hypothesis'],
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output_column='label',
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)
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anli_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template={
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'A':
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dict(round=[
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dict(role='HUMAN', prompt='{context}\n{hypothesis}\What is the relation between the two sentences?'),
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dict(role='BOT', prompt='Contradiction'),
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]),
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'B':
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dict(round=[
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dict(role='HUMAN', prompt='{context}\n{hypothesis}\What is the relation between the two sentences?'),
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dict(role='BOT', prompt='Entailment'),
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]),
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'C':
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dict(round=[
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dict(role='HUMAN', prompt='{context}\n{hypothesis}\What is the relation between the two sentences?'),
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dict(role='BOT', prompt='Neutral'),
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]),
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},
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=PPLInferencer),
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)
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anli_eval_cfg = dict(evaluator=dict(type=AccEvaluator), )
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anli_datasets.append(
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dict(
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type=AnliDataset,
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abbr=f'anli-{_split}',
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path=f'data/anli/anli_v1.0/{_split}/dev.jsonl',
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reader_cfg=anli_reader_cfg,
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infer_cfg=anli_infer_cfg,
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eval_cfg=anli_eval_cfg,
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)
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)
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