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Unverified Commit aa2dd2b5 authored by Fengzhe Zhou's avatar Fengzhe Zhou Committed by GitHub
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[Format] Add config lints (#892)

parent 3dbba119
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Showing with 149 additions and 149 deletions
configs/datasets/anthropics_evals/sycophancy_gen_4bba45.py
View file @ aa2dd2b5
...@@ -24,7 +24,7 @@ sycophancy_infer_cfg = dict( ...@@ -24,7 +24,7 @@ sycophancy_infer_cfg = dict(
sycophancy_eval_cfg = dict( sycophancy_eval_cfg = dict(
evaluator=dict(type=AccEvaluator), evaluator=dict(type=AccEvaluator),
pred_role="BOT", pred_role='BOT',
pred_postprocessor=dict(type=first_option_postprocess, options='ABCDEFG'), pred_postprocessor=dict(type=first_option_postprocess, options='ABCDEFG'),
) )
......
configs/datasets/apps/README.md
View file @ aa2dd2b5
...@@ -26,11 +26,11 @@ print(next(iter(ds))["question"]) ...@@ -26,11 +26,11 @@ print(next(iter(ds))["question"])
## Evaluation results ## Evaluation results
| dataset | metric | CodeLlama-7b-Python | internlm2-chat-1.8b-sft-hf | internlm2-chat-7b-sft-hf | internlm2-chat-20b-sft-hf | | dataset | metric | CodeLlama-7b-Python | internlm2-chat-1.8b-sft-hf | internlm2-chat-7b-sft-hf | internlm2-chat-20b-sft-hf |
|-----------------------|----------|-------------|-------------|-------------|-------------| |-----------------------|----------|-------------|-------------|-------------|-------------|
| apps_mini | pass@1 | 1.3 | 0.7 | 7.1 | 9.3 | | apps_mini | pass@1 | 1.3 | 0.7 | 7.1 | 9.3 |
Please refer to Table 3 of [code llama](https://scontent-nrt1-2.xx.fbcdn.net/v/t39.2365-6/369856151_1754812304950972_1159666448927483931_n.pdf?_nc_cat=107&ccb=1-7&_nc_sid=3c67a6&_nc_ohc=TxT1PKkNBZoAX8zMHbm&_nc_ht=scontent-nrt1-2.xx&oh=00_AfDmmQAPzqX1-QOKIDUV5lGKzaZqt0CZUVtxFjHtnh6ycQ&oe=65F5AF8F) for original results if needed. Please refer to Table 3 of [code llama](https://scontent-nrt1-2.xx.fbcdn.net/v/t39.2365-6/369856151_1754812304950972_1159666448927483931_n.pdf?_nc_cat=107&ccb=1-7&_nc_sid=3c67a6&_nc_ohc=TxT1PKkNBZoAX8zMHbm&_nc_ht=scontent-nrt1-2.xx&oh=00_AfDmmQAPzqX1-QOKIDUV5lGKzaZqt0CZUVtxFjHtnh6ycQ&oe=65F5AF8F) for original results if needed.
## Citation ## Citation
``` ```
...@@ -40,4 +40,4 @@ Please refer to Table 3 of [code llama](https://scontent-nrt1-2.xx.fbcdn.net/v/t ...@@ -40,4 +40,4 @@ Please refer to Table 3 of [code llama](https://scontent-nrt1-2.xx.fbcdn.net/v/t
journal={NeurIPS}, journal={NeurIPS},
year={2021} year={2021}
} }
``` ```
\ No newline at end of file
configs/datasets/apps/apps_gen_c7893a.py
View file @ aa2dd2b5
...@@ -3,23 +3,23 @@ from opencompass.openicl.icl_retriever import ZeroRetriever ...@@ -3,23 +3,23 @@ from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import APPSDataset, APPSEvaluator from opencompass.datasets import APPSDataset, APPSEvaluator
APPS_reader_cfg = dict(input_columns=["question", "starter"], output_column="problem_id", train_split='test') APPS_reader_cfg = dict(input_columns=['question', 'starter'], output_column='problem_id', train_split='test')
APPS_infer_cfg = dict( APPS_infer_cfg = dict(
prompt_template=dict( prompt_template=dict(
type=PromptTemplate, type=PromptTemplate,
template="Please write a python program to address the following QUESTION. Your ANSWER should be in a code block format like this: ```python # Write your code here ```. \nQUESTION:\n{question} {starter}\nANSWER:\n"), template='Please write a python program to address the following QUESTION. Your ANSWER should be in a code block format like this: ```python # Write your code here ```. \nQUESTION:\n{question} {starter}\nANSWER:\n'),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512), inferencer=dict(type=GenInferencer, max_out_len=512),
) )
APPS_eval_cfg = dict(evaluator=dict(type=APPSEvaluator), pred_role="BOT") APPS_eval_cfg = dict(evaluator=dict(type=APPSEvaluator), pred_role='BOT')
APPS_datasets = [ APPS_datasets = [
dict( dict(
type=APPSDataset, type=APPSDataset,
abbr="apps", abbr='apps',
path="codeparrot/apps", path='codeparrot/apps',
num_repeats=1, num_repeats=1,
reader_cfg=APPS_reader_cfg, reader_cfg=APPS_reader_cfg,
infer_cfg=APPS_infer_cfg, infer_cfg=APPS_infer_cfg,
......
configs/datasets/apps/apps_mini_gen.py
View file @ aa2dd2b5
from mmengine.config import read_base from mmengine.config import read_base
with read_base(): with read_base():
from .apps_mini_gen_c7893a import APPS_datasets # noqa: F401, F403 from .apps_mini_gen_c7893a import APPS_datasets # noqa: F401, F403
\ No newline at end of file
configs/datasets/apps/apps_mini_gen_c7893a.py
View file @ aa2dd2b5
...@@ -3,23 +3,23 @@ from opencompass.openicl.icl_retriever import ZeroRetriever ...@@ -3,23 +3,23 @@ from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import APPS_miniDataset, APPSEvaluator from opencompass.datasets import APPS_miniDataset, APPSEvaluator
APPS_reader_cfg = dict(input_columns=["question", "starter"], output_column="problem_id", train_split='test') APPS_reader_cfg = dict(input_columns=['question', 'starter'], output_column='problem_id', train_split='test')
APPS_infer_cfg = dict( APPS_infer_cfg = dict(
prompt_template=dict( prompt_template=dict(
type=PromptTemplate, type=PromptTemplate,
template="Please write a python program to address the following QUESTION. Your ANSWER should be in a code block format like this: ```python # Write your code here ```. \nQUESTION:\n{question} {starter}\nANSWER:\n"), template='Please write a python program to address the following QUESTION. Your ANSWER should be in a code block format like this: ```python # Write your code here ```. \nQUESTION:\n{question} {starter}\nANSWER:\n'),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512), inferencer=dict(type=GenInferencer, max_out_len=512),
) )
APPS_eval_cfg = dict(evaluator=dict(type=APPSEvaluator), pred_role="BOT") APPS_eval_cfg = dict(evaluator=dict(type=APPSEvaluator), pred_role='BOT')
APPS_mini_datasets = [ APPS_mini_datasets = [
dict( dict(
type=APPS_miniDataset, type=APPS_miniDataset,
abbr="apps_mini", abbr='apps_mini',
path="./data/apps_mini", path='./data/apps_mini',
num_repeats=1, num_repeats=1,
reader_cfg=APPS_reader_cfg, reader_cfg=APPS_reader_cfg,
infer_cfg=APPS_infer_cfg, infer_cfg=APPS_infer_cfg,
......
configs/datasets/bbh/bbh_gen_0a5495.py
View file @ aa2dd2b5
...@@ -5,7 +5,7 @@ from opencompass.openicl.icl_inferencer import GenInferencer ...@@ -5,7 +5,7 @@ from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import BBHDataset, BBHEvaluator, bbh_mcq_postprocess, BBHEvaluator_mcq from opencompass.datasets import BBHDataset, BBHEvaluator, bbh_mcq_postprocess, BBHEvaluator_mcq
bbh_reader_cfg = dict(input_columns=["input"], output_column="target") bbh_reader_cfg = dict(input_columns=['input'], output_column='target')
bbh_multiple_choice_sets = [ bbh_multiple_choice_sets = [
'temporal_sequences', 'temporal_sequences',
...@@ -52,14 +52,14 @@ for _name in bbh_multiple_choice_sets: ...@@ -52,14 +52,14 @@ for _name in bbh_multiple_choice_sets:
inferencer=dict(type=GenInferencer, max_out_len=512)) inferencer=dict(type=GenInferencer, max_out_len=512))
bbh_eval_cfg = dict( bbh_eval_cfg = dict(
evaluator=dict(type=BBHEvaluator_mcq), evaluator=dict(type=BBHEvaluator_mcq),
pred_role="BOT", pred_role='BOT',
pred_postprocessor=dict(type=bbh_mcq_postprocess), pred_postprocessor=dict(type=bbh_mcq_postprocess),
dataset_postprocessor=dict(type=bbh_mcq_postprocess)) dataset_postprocessor=dict(type=bbh_mcq_postprocess))
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path=f"./data/BBH/data", path=f'./data/BBH/data',
name=_name, name=_name,
abbr='bbh-' + _name, abbr='bbh-' + _name,
reader_cfg=bbh_reader_cfg, reader_cfg=bbh_reader_cfg,
...@@ -76,12 +76,12 @@ for _name in bbh_free_form_sets: ...@@ -76,12 +76,12 @@ for _name in bbh_free_form_sets:
), ),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512)) inferencer=dict(type=GenInferencer, max_out_len=512))
bbh_eval_cfg = dict(evaluator=dict(type=BBHEvaluator), pred_role="BOT") bbh_eval_cfg = dict(evaluator=dict(type=BBHEvaluator), pred_role='BOT')
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path=f"./data/BBH/data", path=f'./data/BBH/data',
name=_name, name=_name,
abbr='bbh-' + _name, abbr='bbh-' + _name,
reader_cfg=bbh_reader_cfg, reader_cfg=bbh_reader_cfg,
......
configs/datasets/bbh/bbh_gen_2879b0.py
View file @ aa2dd2b5
...@@ -23,11 +23,11 @@ for name, test_type in settings: ...@@ -23,11 +23,11 @@ for name, test_type in settings:
desc = task_prompt.strip() + '\n' desc = task_prompt.strip() + '\n'
else: else:
desc = '' desc = ''
prompt_rounds.append(dict(role="HUMAN", prompt=f"{desc}{question.strip()}")) prompt_rounds.append(dict(role='HUMAN', prompt=f'{desc}{question.strip()}'))
prompt_rounds.append(dict(role="BOT", prompt=answer.strip())) prompt_rounds.append(dict(role='BOT', prompt=answer.strip()))
prompt_rounds.append(dict(role="HUMAN", prompt="Q: {input}")) prompt_rounds.append(dict(role='HUMAN', prompt='Q: {input}'))
bbh_reader_cfg = dict(input_columns=["input"], output_column="target") bbh_reader_cfg = dict(input_columns=['input'], output_column='target')
bbh_infer_cfg = dict( bbh_infer_cfg = dict(
prompt_template=dict(type=PromptTemplate, template=dict(round=prompt_rounds)), prompt_template=dict(type=PromptTemplate, template=dict(round=prompt_rounds)),
...@@ -37,18 +37,18 @@ for name, test_type in settings: ...@@ -37,18 +37,18 @@ for name, test_type in settings:
if test_type == 'mcq': if test_type == 'mcq':
bbh_eval_cfg = dict( bbh_eval_cfg = dict(
evaluator=dict(type=BBHEvaluator_mcq), evaluator=dict(type=BBHEvaluator_mcq),
pred_role="BOT", pred_role='BOT',
pred_postprocessor=dict(type=bbh_mcq_postprocess), pred_postprocessor=dict(type=bbh_mcq_postprocess),
dataset_postprocessor=dict(type=bbh_mcq_postprocess)) dataset_postprocessor=dict(type=bbh_mcq_postprocess))
else: else:
bbh_eval_cfg = dict( bbh_eval_cfg = dict(
evaluator=dict(type=BBHEvaluator), evaluator=dict(type=BBHEvaluator),
pred_role="BOT") pred_role='BOT')
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path="./data/BBH/data", path='./data/BBH/data',
name=name, name=name,
abbr='bbh-' + name, abbr='bbh-' + name,
reader_cfg=bbh_reader_cfg.copy(), reader_cfg=bbh_reader_cfg.copy(),
......
configs/datasets/bbh/bbh_gen_5b92b0.py
View file @ aa2dd2b5
...@@ -5,7 +5,7 @@ from opencompass.openicl.icl_inferencer import GenInferencer ...@@ -5,7 +5,7 @@ from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import BBHDataset, BBHEvaluator, bbh_mcq_postprocess, BBHEvaluator_mcq from opencompass.datasets import BBHDataset, BBHEvaluator, bbh_mcq_postprocess, BBHEvaluator_mcq
bbh_reader_cfg = dict(input_columns=["input"], output_column="target") bbh_reader_cfg = dict(input_columns=['input'], output_column='target')
bbh_multiple_choice_sets = [ bbh_multiple_choice_sets = [
'temporal_sequences', 'temporal_sequences',
...@@ -48,7 +48,7 @@ for _name in bbh_multiple_choice_sets: ...@@ -48,7 +48,7 @@ for _name in bbh_multiple_choice_sets:
type=PromptTemplate, type=PromptTemplate,
template=dict(round=[ template=dict(round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: Let's think step by step." f"Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: Let's think step by step."
) )
...@@ -57,14 +57,14 @@ for _name in bbh_multiple_choice_sets: ...@@ -57,14 +57,14 @@ for _name in bbh_multiple_choice_sets:
inferencer=dict(type=GenInferencer, max_out_len=512)) inferencer=dict(type=GenInferencer, max_out_len=512))
bbh_eval_cfg = dict( bbh_eval_cfg = dict(
evaluator=dict(type=BBHEvaluator_mcq), evaluator=dict(type=BBHEvaluator_mcq),
pred_role="BOT", pred_role='BOT',
pred_postprocessor=dict(type=bbh_mcq_postprocess), pred_postprocessor=dict(type=bbh_mcq_postprocess),
dataset_postprocessor=dict(type=bbh_mcq_postprocess)) dataset_postprocessor=dict(type=bbh_mcq_postprocess))
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path=f"./data/BBH/data", path=f'./data/BBH/data',
name=_name, name=_name,
abbr='bbh-' + _name, abbr='bbh-' + _name,
reader_cfg=bbh_reader_cfg, reader_cfg=bbh_reader_cfg,
...@@ -79,19 +79,19 @@ for _name in bbh_free_form_sets: ...@@ -79,19 +79,19 @@ for _name in bbh_free_form_sets:
type=PromptTemplate, type=PromptTemplate,
template=dict(round=[ template=dict(round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: Let's think step by step." f"Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: Let's think step by step."
) )
])), ])),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512)) inferencer=dict(type=GenInferencer, max_out_len=512))
bbh_eval_cfg = dict(evaluator=dict(type=BBHEvaluator), pred_role="BOT") bbh_eval_cfg = dict(evaluator=dict(type=BBHEvaluator), pred_role='BOT')
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path=f"./data/BBH/data", path=f'./data/BBH/data',
name=_name, name=_name,
abbr='bbh-' + _name, abbr='bbh-' + _name,
reader_cfg=bbh_reader_cfg, reader_cfg=bbh_reader_cfg,
......
configs/datasets/bbh/bbh_gen_5bf00b.py
View file @ aa2dd2b5
...@@ -5,7 +5,7 @@ from opencompass.openicl.icl_inferencer import GenInferencer ...@@ -5,7 +5,7 @@ from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import BBHDataset, BBHEvaluator, bbh_mcq_postprocess, BBHEvaluator_mcq from opencompass.datasets import BBHDataset, BBHEvaluator, bbh_mcq_postprocess, BBHEvaluator_mcq
bbh_reader_cfg = dict(input_columns=["input"], output_column="target") bbh_reader_cfg = dict(input_columns=['input'], output_column='target')
bbh_multiple_choice_sets = [ bbh_multiple_choice_sets = [
'temporal_sequences', 'temporal_sequences',
...@@ -48,23 +48,23 @@ for _name in bbh_multiple_choice_sets: ...@@ -48,23 +48,23 @@ for _name in bbh_multiple_choice_sets:
type=PromptTemplate, type=PromptTemplate,
template=dict(round=[ template=dict(round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: " f'Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: '
) )
])), ])),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512)) inferencer=dict(type=GenInferencer, max_out_len=512))
bbh_eval_cfg = dict( bbh_eval_cfg = dict(
evaluator=dict(type=BBHEvaluator_mcq), evaluator=dict(type=BBHEvaluator_mcq),
pred_role="BOT", pred_role='BOT',
pred_postprocessor=dict(type=bbh_mcq_postprocess), pred_postprocessor=dict(type=bbh_mcq_postprocess),
dataset_postprocessor=dict(type=bbh_mcq_postprocess)) dataset_postprocessor=dict(type=bbh_mcq_postprocess))
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path=f"./data/BBH/data", path=f'./data/BBH/data',
name=_name, name=_name,
abbr='bbh-' + _name, abbr='bbh-' + _name,
reader_cfg=bbh_reader_cfg, reader_cfg=bbh_reader_cfg,
...@@ -79,19 +79,19 @@ for _name in bbh_free_form_sets: ...@@ -79,19 +79,19 @@ for _name in bbh_free_form_sets:
type=PromptTemplate, type=PromptTemplate,
template=dict(round=[ template=dict(round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: " f'Follow the given examples and answer the question.\n{_hint}\n\nQ: {{input}}\nA: '
) )
])), ])),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=512)) inferencer=dict(type=GenInferencer, max_out_len=512))
bbh_eval_cfg = dict(evaluator=dict(type=BBHEvaluator), pred_role="BOT") bbh_eval_cfg = dict(evaluator=dict(type=BBHEvaluator), pred_role='BOT')
bbh_datasets.append( bbh_datasets.append(
dict( dict(
type=BBHDataset, type=BBHDataset,
path=f"./data/BBH/data", path=f'./data/BBH/data',
name=_name, name=_name,
abbr='bbh-' + _name, abbr='bbh-' + _name,
reader_cfg=bbh_reader_cfg, reader_cfg=bbh_reader_cfg,
......
configs/datasets/ceval/ceval_clean_ppl.py
View file @ aa2dd2b5
...@@ -62,7 +62,7 @@ ceval_subject_mapping = { ...@@ -62,7 +62,7 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val"]: for _split in ['val']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
...@@ -70,18 +70,18 @@ for _split in ["val"]: ...@@ -70,18 +70,18 @@ for _split in ["val"]:
type=PromptTemplate, type=PromptTemplate,
template={ template={
answer: dict( answer: dict(
begin="</E>", begin='</E>',
round=[ round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: " f'以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: '
), ),
dict(role="BOT", prompt=answer), dict(role='BOT', prompt=answer),
]) ])
for answer in ["A", "B", "C", "D"] for answer in ['A', 'B', 'C', 'D']
}, },
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=PPLInferencer), inferencer=dict(type=PPLInferencer),
...@@ -92,13 +92,13 @@ for _split in ["val"]: ...@@ -92,13 +92,13 @@ for _split in ["val"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + _name, abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' + _name,
reader_cfg=dict( reader_cfg=dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split), test_split=_split),
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_gen_2daf24.py
View file @ aa2dd2b5
...@@ -62,23 +62,23 @@ ceval_subject_mapping = { ...@@ -62,23 +62,23 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val", "test"]: for _split in ['val', 'test']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
ice_template=dict( ice_template=dict(
type=PromptTemplate, type=PromptTemplate,
template=dict( template=dict(
begin="</E>", begin='</E>',
round=[ round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: " f'以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: '
), ),
dict(role="BOT", prompt="{answer}"), dict(role='BOT', prompt='{answer}'),
]), ]),
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=GenInferencer), inferencer=dict(type=GenInferencer),
...@@ -91,14 +91,14 @@ for _split in ["val", "test"]: ...@@ -91,14 +91,14 @@ for _split in ["val", "test"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' +
_name, _name,
reader_cfg=dict( reader_cfg=dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split), test_split=_split),
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_gen_5f30c7.py
View file @ aa2dd2b5
...@@ -62,23 +62,23 @@ ceval_subject_mapping = { ...@@ -62,23 +62,23 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val"]: for _split in ['val']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
ice_template=dict( ice_template=dict(
type=PromptTemplate, type=PromptTemplate,
template=dict( template=dict(
begin="</E>", begin='</E>',
round=[ round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: " f'以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: '
), ),
dict(role="BOT", prompt="{answer}"), dict(role='BOT', prompt='{answer}'),
]), ]),
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=GenInferencer), inferencer=dict(type=GenInferencer),
...@@ -91,14 +91,14 @@ for _split in ["val"]: ...@@ -91,14 +91,14 @@ for _split in ["val"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' +
_name, _name,
reader_cfg=dict( reader_cfg=dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split), test_split=_split),
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_internal_ppl_1cd8bf.py
View file @ aa2dd2b5
...@@ -61,28 +61,28 @@ ceval_subject_mapping = { ...@@ -61,28 +61,28 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val", "test"]: for _split in ['val', 'test']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
ceval_reader_cfg = dict( ceval_reader_cfg = dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split, test_split=_split,
) )
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
hint = f"以下是关于{_ch_name}的单项选择题，请直接给出正确答案的选项。" hint = f'以下是关于{_ch_name}的单项选择题，请直接给出正确答案的选项。'
question_and_options = "{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}" question_and_options = '{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}'
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
ice_template=dict( ice_template=dict(
type=PromptTemplate, type=PromptTemplate,
template={answer: f"{question_and_options}\n答案: {answer}\n" for answer in ["A", "B", "C", "D"]}, template={answer: f'{question_and_options}\n答案: {answer}\n' for answer in ['A', 'B', 'C', 'D']},
), ),
prompt_template=dict( prompt_template=dict(
type=PromptTemplate, type=PromptTemplate,
template={answer: f"{hint}\n</E>{question_and_options}\n答案: {answer}" for answer in ["A", "B", "C", "D"]}, template={answer: f'{hint}\n</E>{question_and_options}\n答案: {answer}' for answer in ['A', 'B', 'C', 'D']},
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=PPLInferencer), inferencer=dict(type=PPLInferencer),
...@@ -93,9 +93,9 @@ for _split in ["val", "test"]: ...@@ -93,9 +93,9 @@ for _split in ["val", "test"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval_internal/formal_ceval", path='./data/ceval_internal/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + _name, abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' + _name,
reader_cfg=ceval_reader_cfg, reader_cfg=ceval_reader_cfg,
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_ppl_1cd8bf.py
View file @ aa2dd2b5
...@@ -61,28 +61,28 @@ ceval_subject_mapping = { ...@@ -61,28 +61,28 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val", "test"]: for _split in ['val', 'test']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
ceval_reader_cfg = dict( ceval_reader_cfg = dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split, test_split=_split,
) )
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
hint = f"以下是关于{_ch_name}的单项选择题，请直接给出正确答案的选项。" hint = f'以下是关于{_ch_name}的单项选择题，请直接给出正确答案的选项。'
question_and_options = "{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}" question_and_options = '{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}'
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
ice_template=dict( ice_template=dict(
type=PromptTemplate, type=PromptTemplate,
template={answer: f"{question_and_options}\n答案: {answer}\n" for answer in ["A", "B", "C", "D"]}, template={answer: f'{question_and_options}\n答案: {answer}\n' for answer in ['A', 'B', 'C', 'D']},
), ),
prompt_template=dict( prompt_template=dict(
type=PromptTemplate, type=PromptTemplate,
template={answer: f"{hint}\n</E>{question_and_options}\n答案: {answer}" for answer in ["A", "B", "C", "D"]}, template={answer: f'{hint}\n</E>{question_and_options}\n答案: {answer}' for answer in ['A', 'B', 'C', 'D']},
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=PPLInferencer), inferencer=dict(type=PPLInferencer),
...@@ -93,9 +93,9 @@ for _split in ["val", "test"]: ...@@ -93,9 +93,9 @@ for _split in ["val", "test"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + _name, abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' + _name,
reader_cfg=ceval_reader_cfg, reader_cfg=ceval_reader_cfg,
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_ppl_578f8d.py
View file @ aa2dd2b5
...@@ -61,7 +61,7 @@ ceval_subject_mapping = { ...@@ -61,7 +61,7 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val"]: for _split in ['val']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
...@@ -69,18 +69,18 @@ for _split in ["val"]: ...@@ -69,18 +69,18 @@ for _split in ["val"]:
type=PromptTemplate, type=PromptTemplate,
template={ template={
answer: dict( answer: dict(
begin="</E>", begin='</E>',
round=[ round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: " f'以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: '
), ),
dict(role="BOT", prompt=answer), dict(role='BOT', prompt=answer),
]) ])
for answer in ["A", "B", "C", "D"] for answer in ['A', 'B', 'C', 'D']
}, },
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=PPLInferencer), inferencer=dict(type=PPLInferencer),
...@@ -91,14 +91,14 @@ for _split in ["val"]: ...@@ -91,14 +91,14 @@ for _split in ["val"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' +
_name, _name,
reader_cfg=dict( reader_cfg=dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split), test_split=_split),
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_ppl_93e5ce.py
View file @ aa2dd2b5
...@@ -61,7 +61,7 @@ ceval_subject_mapping = { ...@@ -61,7 +61,7 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val", "test"]: for _split in ['val', 'test']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
...@@ -69,18 +69,18 @@ for _split in ["val", "test"]: ...@@ -69,18 +69,18 @@ for _split in ["val", "test"]:
type=PromptTemplate, type=PromptTemplate,
template={ template={
answer: dict( answer: dict(
begin="</E>", begin='</E>',
round=[ round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: " f'以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n答案: '
), ),
dict(role="BOT", prompt=answer), dict(role='BOT', prompt=answer),
]) ])
for answer in ["A", "B", "C", "D"] for answer in ['A', 'B', 'C', 'D']
}, },
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]), retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
inferencer=dict(type=PPLInferencer), inferencer=dict(type=PPLInferencer),
...@@ -91,14 +91,14 @@ for _split in ["val", "test"]: ...@@ -91,14 +91,14 @@ for _split in ["val", "test"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' +
_name, _name,
reader_cfg=dict( reader_cfg=dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split), test_split=_split),
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/ceval/ceval_zero_shot_gen_bd40ef.py
View file @ aa2dd2b5
...@@ -62,23 +62,23 @@ ceval_subject_mapping = { ...@@ -62,23 +62,23 @@ ceval_subject_mapping = {
ceval_all_sets = list(ceval_subject_mapping.keys()) ceval_all_sets = list(ceval_subject_mapping.keys())
ceval_datasets = [] ceval_datasets = []
for _split in ["val"]: for _split in ['val']:
for _name in ceval_all_sets: for _name in ceval_all_sets:
_ch_name = ceval_subject_mapping[_name][1] _ch_name = ceval_subject_mapping[_name][1]
ceval_infer_cfg = dict( ceval_infer_cfg = dict(
ice_template=dict( ice_template=dict(
type=PromptTemplate, type=PromptTemplate,
template=dict( template=dict(
begin="</E>", begin='</E>',
round=[ round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt= prompt=
f"以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n让我们一步一步思考。答案: " f'以下是中国关于{_ch_name}考试的单项选择题，请选出其中的正确答案。\n{{question}}\nA. {{A}}\nB. {{B}}\nC. {{C}}\nD. {{D}}\n让我们一步一步思考。答案: '
), ),
dict(role="BOT", prompt="{answer}"), dict(role='BOT', prompt='{answer}'),
]), ]),
ice_token="</E>", ice_token='</E>',
), ),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer, max_out_len=256), inferencer=dict(type=GenInferencer, max_out_len=256),
...@@ -91,14 +91,14 @@ for _split in ["val"]: ...@@ -91,14 +91,14 @@ for _split in ["val"]:
ceval_datasets.append( ceval_datasets.append(
dict( dict(
type=CEvalDataset, type=CEvalDataset,
path="./data/ceval/formal_ceval", path='./data/ceval/formal_ceval',
name=_name, name=_name,
abbr="ceval-" + _name if _split == "val" else "ceval-test-" + abbr='ceval-' + _name if _split == 'val' else 'ceval-test-' +
_name, _name,
reader_cfg=dict( reader_cfg=dict(
input_columns=["question", "A", "B", "C", "D"], input_columns=['question', 'A', 'B', 'C', 'D'],
output_column="answer", output_column='answer',
train_split="dev", train_split='dev',
test_split=_split), test_split=_split),
infer_cfg=ceval_infer_cfg, infer_cfg=ceval_infer_cfg,
eval_cfg=ceval_eval_cfg, eval_cfg=ceval_eval_cfg,
......
configs/datasets/civilcomments/civilcomments_clp_a3c5fd.py
View file @ aa2dd2b5
...@@ -15,10 +15,10 @@ civilcomments_infer_cfg = dict( ...@@ -15,10 +15,10 @@ civilcomments_infer_cfg = dict(
type=PromptTemplate, type=PromptTemplate,
template=dict(round=[ template=dict(round=[
dict( dict(
role="HUMAN", role='HUMAN',
prompt="Text: {text}\nQuestion: Does the above text contain " prompt='Text: {text}\nQuestion: Does the above text contain '
"rude, hateful, aggressive, disrespectful or unreasonable " 'rude, hateful, aggressive, disrespectful or unreasonable '
"language?\nAnswer:") 'language?\nAnswer:')
])), ])),
retriever=dict(type=ZeroRetriever), retriever=dict(type=ZeroRetriever),
inferencer=dict(type=CLPInferencer)) inferencer=dict(type=CLPInferencer))
......
configs/datasets/clozeTest_maxmin/clozeTest_maxmin_gen.py
View file @ aa2dd2b5
from mmengine.config import read_base from mmengine.config import read_base
with read_base(): with read_base():
from .clozeTest_maxmin_gen_c205fb import maxmin_datasets # noqa: F401, F403 from .clozeTest_maxmin_gen_c205fb import maxmin_datasets # noqa: F401, F403
\ No newline at end of file
configs/datasets/clozeTest_maxmin/clozeTest_maxmin_gen_c205fb.py
View file @ aa2dd2b5
...@@ -7,8 +7,8 @@ from opencompass.utils.text_postprocessors import first_capital_postprocess ...@@ -7,8 +7,8 @@ from opencompass.utils.text_postprocessors import first_capital_postprocess
maxmin_reader_cfg = dict( maxmin_reader_cfg = dict(
input_columns=["nl_tokens", "pl_tokens"], input_columns=['nl_tokens', 'pl_tokens'],
output_column="answer", output_column='answer',
) )
maxmin_infer_cfg = dict( maxmin_infer_cfg = dict(
...@@ -16,8 +16,8 @@ maxmin_infer_cfg = dict( ...@@ -16,8 +16,8 @@ maxmin_infer_cfg = dict(
type=PromptTemplate, type=PromptTemplate,
template=dict( template=dict(
round=[ round=[
dict(role="HUMAN", prompt="Code:{pl_tokens}\nThe aim of the code: {nl_tokens}\nQuestion: Please tell me what \"<mask>\" in the code should be replaced with and you must response to me only A or B.\nA. max\nB. min\nAnswer:"), dict(role='HUMAN', prompt="Code:{pl_tokens}\nThe aim of the code: {nl_tokens}\nQuestion: Please tell me what \"<mask>\" in the code should be replaced with and you must response to me only A or B.\nA. max\nB. min\nAnswer:"),
dict(role="BOT", prompt="{answer}"), dict(role='BOT', prompt='{answer}'),
] ]
), ),
), ),
...@@ -26,17 +26,17 @@ maxmin_infer_cfg = dict( ...@@ -26,17 +26,17 @@ maxmin_infer_cfg = dict(
) )
maxmin_eval_cfg = dict(evaluator=dict(type=AccEvaluator), maxmin_eval_cfg = dict(evaluator=dict(type=AccEvaluator),
pred_role="BOT", pred_role='BOT',
pred_postprocessor=dict(type=first_capital_postprocess)) pred_postprocessor=dict(type=first_capital_postprocess))
maxmin_datasets = [ maxmin_datasets = [
dict( dict(
type=MaxminDataset, type=MaxminDataset,
abbr=f"maxmin", abbr=f'maxmin',
test_path=f"data/clozeTest-maxmin/python/clozeTest.json", test_path=f'data/clozeTest-maxmin/python/clozeTest.json',
answer_path=f"data/clozeTest-maxmin/python/answers.txt", answer_path=f'data/clozeTest-maxmin/python/answers.txt',
reader_cfg=maxmin_reader_cfg, reader_cfg=maxmin_reader_cfg,
infer_cfg=maxmin_infer_cfg, infer_cfg=maxmin_infer_cfg,
eval_cfg=maxmin_eval_cfg, eval_cfg=maxmin_eval_cfg,
) )
] ]
\ No newline at end of file
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