OpenCompass/opencompass/configs/datasets/PMMEval/mifeval_gen_79f8fb.py
Linchen Xiao a6193b4c02
[Refactor] Code refactoarization (#1831)
* Update

* fix lint

* update

* fix lint
2025-01-20 19:17:38 +08:00

52 lines
1.5 KiB
Python
Executable File

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets.PMMEval import PMMEvalMIFEvalDataset, PMMEvalMIFEvalEvaluator, pmmeval_mifeval_postprocess
NATURAL_LANGUAGE_CODES = ['en', 'zh', 'ar', 'es', 'fr', 'ja', 'ko', 'pt', 'th', 'vi']
PMMEVAL_MIFEVAL_TEMPLATE = '{prompt}'
PMMEval_MIFEval_datasets = list()
PMMEval_MIFEval_reader_cfg = dict(
input_columns=['prompt', 'instruction_id_list', 'kwargs'],
output_column=None,
test_split='test'
)
PMMEval_MIFEval_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(
role='HUMAN',
prompt=PMMEVAL_MIFEVAL_TEMPLATE
)
]
)
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer),
)
for lang_code in NATURAL_LANGUAGE_CODES:
PMMEval_MIFEval_eval_cfg = dict(
evaluator=dict(type=PMMEvalMIFEvalEvaluator),
pred_role='BOT',
pred_postprocessor=dict(type=pmmeval_mifeval_postprocess, lang_code=lang_code)
)
PMMEval_MIFEval_datasets.append(
dict(
abbr=f'mifeval-{lang_code}',
type=PMMEvalMIFEvalDataset,
path='P-MMEval',
lang=lang_code,
reader_cfg=PMMEval_MIFEval_reader_cfg,
infer_cfg=PMMEval_MIFEval_infer_cfg,
eval_cfg=PMMEval_MIFEval_eval_cfg)
)