code: def __init__(
      self,
      params=None,
      lr=0.01,
      lambd=0.0001,
      alpha=0.75,
      t0=1000000.0,
      weight_decay=0,
      foreach=None,
      maximize=False,
  ):
      TorchOptimizer.__init__(self)
      self.param_dict["lr"] = lr
      self.param_dict["lambd"] = lambd
      self.param_dict["alpha"] = alpha
      self.param_dict["t0"] = t0
      self.param_dict["weight_decay"] = weight_decay
      self.param_dict["foreach"] = foreach
      self.param_dict["maximize"] = maximize
      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 ASGD object from inherited base classes: optim, TorchOptimizer with example: obj = ASGD(params, lr, lambd, alpha, t0, weight_decay, foreach, maximize)