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reactivate default imports for PropositionalLogicDataset

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Andreas Koepf 2025-02-21 15:41:04 +01:00
parent 78b2b518d9
commit 222d5ebf94
2 changed files with 5 additions and 7 deletions
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10
reasoning_gym/logic/__init__.py
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@ -4,21 +4,19 @@ Logic tasks for training reasoning capabilities.
from .aiw import AliceInWonderlandConfig, AliceInWonderlandDataset from .aiw import AliceInWonderlandConfig, AliceInWonderlandDataset
from .circuit_logic import CircuitLogicConfig, CircuitLogicDataset from .circuit_logic import CircuitLogicConfig, CircuitLogicDataset
from .propositional_logic import PropositionalLogicConfig, PropositionalLogicDataset
from .self_reference import SelfReferenceConfig, SelfReferenceDataset from .self_reference import SelfReferenceConfig, SelfReferenceDataset
from .syllogisms import SyllogismConfig, SyllogismDataset, Term from .syllogisms import SyllogismConfig, SyllogismDataset
from .zebra_puzzles import ZebraConfig, ZebraDataset from .zebra_puzzles import ZebraConfig, ZebraDataset
# from .propositional_logic import PropositionalLogicConfig, PropositionalLogicDataset
__all__ = [ __all__ = [
"AliceInWonderlandConfig", "AliceInWonderlandConfig",
"AliceInWonderlandDataset", "AliceInWonderlandDataset",
# "PropositionalLogicConfig", "PropositionalLogicConfig",
# "PropositionalLogicDataset", "PropositionalLogicDataset",
"SyllogismConfig", "SyllogismConfig",
"SyllogismDataset", "SyllogismDataset",
"syllogism_dataset", "syllogism_dataset",
"Term",
"ZebraConfig", "ZebraConfig",
"ZebraDataset", "ZebraDataset",
"SelfReference", "SelfReference",

2
reasoning_gym/logic/propositional_logic.py
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@ -294,7 +294,7 @@ class PropositionalLogicDataset(ProceduralDataset):
else: else:
return 1 + self._measure_complexity(expression.left) + self._measure_complexity(expression.right) return 1 + self._measure_complexity(expression.left) + self._measure_complexity(expression.right)
def score_answer(self, answer: str | None, entry: Dict[str, Any]) -> float: def score_answer(self, answer: str | None, entry: dict[str, Any]) -> float:
"""Robust scoring implementation for propositional logic answers""" """Robust scoring implementation for propositional logic answers"""
if not answer: if not answer:
return 0.0 return 0.0