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39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
from mmengine.config import read_base
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from opencompass.partitioners import NaivePartitioner, NumWorkerPartitioner
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from opencompass.runners import LocalRunner
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from opencompass.tasks import OpenICLEvalTask, OpenICLInferTask
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with read_base():
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from opencompass.configs.datasets.ruler.ruler_combined_gen import \
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ruler_combined_datasets
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from opencompass.configs.models.hf_internlm.lmdeploy_internlm2_5_7b_chat_1m import \
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models as internlm2_5_7b_chat_1m
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from opencompass.configs.summarizers.groups.ruler import \
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ruler_summary_groups
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datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])
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models = internlm2_5_7b_chat_1m
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work_dir = './outputs/ruler'
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infer = dict(
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partitioner=dict(type=NumWorkerPartitioner, num_worker=2),
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runner=dict(type=LocalRunner,
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max_num_workers=16,
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task=dict(type=OpenICLInferTask),
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retry=5),
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)
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eval = dict(
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partitioner=dict(type=NaivePartitioner),
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runner=dict(type=LocalRunner,
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max_num_workers=32,
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task=dict(type=OpenICLEvalTask)),
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)
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summarizer = dict(
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dataset_abbrs=['ruler_4k', 'ruler_8k', 'ruler_16k', 'ruler_32k'],
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summary_groups=sum(
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[v for k, v in locals().items() if k.endswith('_summary_groups')], []),
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)
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