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46cc7894e1
* [Feature] Support import configs/models/summarizers from whl * Update LCBench configs * Update * Update * Update * Update * update * Update * Update * Update * Update * Update
43 lines
1.5 KiB
Python
43 lines
1.5 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.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import AnliDataset
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from opencompass.utils.text_postprocessors import first_capital_postprocess
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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=dict(
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round=[
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dict(role='HUMAN', prompt='{context}\n{hypothesis}\nQuestion: What is the relation between the two sentences?\nA. Contradiction\nB. Entailment\nC. Neutral\nAnswer: '),
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dict(role='BOT', prompt='{label}'),
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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=GenInferencer),
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)
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anli_eval_cfg = dict(evaluator=dict(type=AccEvaluator),
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pred_role='BOT',
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pred_postprocessor=dict(type=first_capital_postprocess))
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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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