class_docstr: RAdam optimizer
docstr: Init
  
  :param params: parameters to optimize
  :param lr: learning rate
  :param betas: beta
  :param eps: numerical precision
  :param weight_decay: weight decay weight
docstr_tok: ["Init",":","param","params",":","parameters","to","optimize",":","param","lr",":","learning","rate",":","param","betas",":","beta",":","param","eps",":","numerical","precision",":","param","weight_decay",":","weight","decay","weight"]
code: def __init__(
      self,
      params,
      lr=1e-3,
      betas=(0.9, 0.999),
      eps=1e-8,
      weight_decay=0,
  ):
      """
      Init
  
      :param params: parameters to optimize
      :param lr: learning rate
      :param betas: beta
      :param eps: numerical precision
      :param weight_decay: weight decay weight
      """
      defaults = dict(
          lr=lr, betas=betas, eps=eps, weight_decay=weight_decay
      )
      self.buffer = [[None, None, None] for _ in range(10)]
      super().__init__(params, defaults)
  
imports: import math
  import torch
  from torch.optim.optimizer import Optimizer
label_desc: Use image node_id 1 to create a new RAdam object from inherited base classes: Optimizer with example: obj = RAdam(params, lr, betas, eps, weight_decay)