code: def __init__(
      self,
      params=None,
      lr=0.001,
      betas=(0.9, 0.999),
      eps=1e-08,
      weight_decay=0.01,
      amsgrad=False,
  ):
      TorchOptimizer.__init__(self)
      self.param_dict["lr"] = lr
      self.param_dict["betas"] = betas
      self.param_dict["eps"] = eps
      self.param_dict["weight_decay"] = weight_decay
      self.param_dict["amsgrad"] = amsgrad
      self.torch_class = type(self).__bases__[0]
  
      if params is None:
          return
  
      params = self.check_params(params)
  
      self.torch_class.__init__(self, params, **self.param_dict)
  
imports: from torch import optim
  from fate.components.components.nn.torch.base import TorchOptimizer
label_desc: Use image node_id 1 to create a new AdamW object from inherited base classes: optim, TorchOptimizer with example: obj = AdamW(params, lr, betas, eps, weight_decay, amsgrad)