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from typing import Any, Dict
from pydantic import BaseModel, ConfigDict
class ExponentialLRParams(BaseModel):
"""Configuration for `torch.optim.lr_scheduler.ExponentialLR`."""
model_config = ConfigDict(frozen=True)
gamma: float = 0.95 # Multiplicative factor of learning rate decay
def asdict(self) -> Dict[str, Any]:
"""Returns a dictionary of valid parameters for `torch.optim.lr_scheduler.ExponentialLR`."""
return self.model_dump()