reasoning-gym/reasoning_gym/factory.py
2025-02-04 19:17:34 +01:00

58 lines
1.7 KiB
Python

from dataclasses import is_dataclass
from typing import Dict, Type, TypeVar
from .dataset import ProceduralDataset
# Type variables for generic type hints
ConfigT = TypeVar("ConfigT")
DatasetT = TypeVar("DatasetT", bound=ProceduralDataset)
# Global registry of datasets
DATASETS: Dict[str, tuple[Type[ProceduralDataset], Type]] = {}
def register_dataset(name: str, dataset_cls: Type[DatasetT], config_cls: Type[ConfigT]) -> None:
"""
Register a dataset class with its configuration class.
Args:
name: Unique identifier for the dataset
dataset_cls: Class derived from ProceduralDataset
config_cls: Configuration dataclass for the dataset
Raises:
ValueError: If name is already registered or invalid types provided
"""
if name in DATASETS:
raise ValueError(f"Dataset '{name}' is already registered")
if not issubclass(dataset_cls, ProceduralDataset):
raise ValueError(f"Dataset class must inherit from ProceduralDataset, got {dataset_cls}")
if not is_dataclass(config_cls):
raise ValueError(f"Config class must be a dataclass, got {config_cls}")
DATASETS[name] = (dataset_cls, config_cls)
def create_dataset(name: str, **kwargs) -> ProceduralDataset:
"""
Create a dataset instance by name with the given configuration.
Args:
name: Registered dataset name
Returns:
Configured dataset instance
Raises:
ValueError: If dataset not found or config type mismatch
"""
if name not in DATASETS:
raise ValueError(f"Dataset '{name}' not registered")
dataset_cls, config_cls = DATASETS[name]
config = config_cls(**kwargs)
return dataset_cls(config=config)