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							17 lines
						
					
					
						
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							17 lines
						
					
					
						
							761 B
						
					
					
				import torch
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from typing import Any, Dict, Tuple
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from pydantic import BaseModel, ConfigDict
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class AdamWParams(BaseModel):
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    """Configuration for `torch.optim.AdamW` optimizer."""
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    model_config = ConfigDict(frozen=True)
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    lr: float = 1e-3                            # Learning rate
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    betas: Tuple[float, ...] = (0.9, 0.999)   # Adam coefficients
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    eps: float = 1e-8                           # Numerical stability
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    weight_decay: float = 1e-2                  # L2 penalty (AdamW uses decoupled weight decay)
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    amsgrad: bool = False                       # Whether to use the AMSGrad variant
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    def asdict(self) -> Dict[str, Any]:
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        """Returns a dictionary of valid parameters for `torch.optim.AdamW`."""
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        return self.model_dump() |