code: def __init__(
      self,
      lr: float = 0.001,
      betas: Tuple[float, float] = (0.9, 0.999),
      eps: float = 1e-8,
      weight_decay: float = 0.01,
      amsgrad: bool = False,
  ) -> None:
      super().__init__()
  
      self._lr = lr
      self._betas = betas
      self._eps = eps
      self._weight_decay = weight_decay
      self._amsgrad = amsgrad
  
file_path: ClassyVision/classy_vision/optim/adamw.py
imports: from typing import Any, Dict, Tuple
  import torch.optim
  from .None import ClassyOptimizer, register_optimizer
label_desc: Use image node_id 1 to create a new AdamW object from inherited base classes: ClassyOptimizer with example: obj = AdamW(lr, betas, eps, weight_decay, amsgrad)