code: def __init__(
      self,
      params,
      lr=1e-3,
      betas=(0.9, 0.999),
      eps=1e-8,
      weight_decay=1e-4,
  ):
      defaults = dict(
          lr=lr, betas=betas, eps=eps, weight_decay=weight_decay
      )
      self.buffer = [[None, None, None] for ind in range(10)]
      super(Ralamb, self).__init__(params, defaults)
  
imports: from torch.optim.optimizer import Optimizer
  import torch
  import math
label_desc: Use image node_id 1 to create a new Ralamb object from inherited base classes: Optimizer with example: obj = Ralamb(params, lr, betas, eps, weight_decay)