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47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
from copy import deepcopy
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from mmengine.config import read_base
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with read_base():
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from opencompass.configs.datasets.agieval.agieval_gen_64afd3 import \
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agieval_datasets
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from opencompass.configs.datasets.bbh.bbh_gen_5b92b0 import bbh_datasets
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from opencompass.configs.datasets.gsm8k.gsm8k_gen_1d7fe4 import \
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gsm8k_datasets
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from opencompass.configs.datasets.humaneval.humaneval_gen_8e312c import \
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humaneval_datasets
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from opencompass.configs.datasets.math.math_evaluatorv2_gen_cecb31 import \
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math_datasets
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from opencompass.configs.datasets.mbpp.deprecated_sanitized_mbpp_gen_1e1056 import \
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sanitized_mbpp_datasets
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from opencompass.configs.datasets.mmlu.mmlu_gen_a484b3 import mmlu_datasets
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from opencompass.configs.models.hf_internlm.hf_internlm2_chat_7b import \
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models as hf_internlm2_chat_7b_model
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from opencompass.configs.models.hf_internlm.hf_internlm2_chat_20b import \
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models as hf_internlm2_chat_20b_model
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from opencompass.configs.summarizers.internlm2_keyset import summarizer
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work_dir = './outputs/internlm2-chat-keyset/'
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_origin_datasets = sum(
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[v for k, v in locals().items() if k.endswith('_datasets')], [])
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_origin_models = sum([v for k, v in locals().items() if k.endswith('_model')],
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[])
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_vanilla_datasets = [deepcopy(d) for d in _origin_datasets]
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_vanilla_models = []
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for m in _origin_models:
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m = deepcopy(m)
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if 'meta_template' in m and 'round' in m['meta_template']:
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round = m['meta_template']['round']
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if any(r['role'] == 'SYSTEM' for r in round):
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new_round = [r for r in round if r['role'] != 'SYSTEM']
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print(
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f'WARNING: remove SYSTEM round in meta_template for {m.get("abbr", None)}'
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)
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m['meta_template']['round'] = new_round
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_vanilla_models.append(m)
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datasets = _vanilla_datasets
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models = _vanilla_models
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