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39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from opencompass.datasets.babilong.babilong import BabiLongDataset, BabiLongEvaluator
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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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babiLong_4k_datasets = []
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split_name='4k'
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max_seq_len=4*1024
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tasks = ['qa1', 'qa2', 'qa3', 'qa4', 'qa5', 'qa6', 'qa7', 'qa8', 'qa9', 'qa10']
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for task in tasks:
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tmp_dataset = {
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'abbr': f'babilong_{task}_{split_name}',
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'type': BabiLongDataset,
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'path': 'opencompass/babilong',
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'task': task,
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'split_name': split_name,
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'reader_cfg': dict(input_columns=['prompt'], output_column='answer'),
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'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='{prompt}'),
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dict(role='BOT', prompt='{answer}\n'),
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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, max_seq_len=max_seq_len),
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),
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'eval_cfg': dict(
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evaluator=dict(type=BabiLongEvaluator),
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),
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}
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babiLong_4k_datasets.append(tmp_dataset)
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