class_docstr: Implements rectified adam as derived in the following paper:
  "On the Variance of the Adaptive Learning Rate and Beyond"
  (https://arxiv.org/abs/1908.03265)
  
  This code is mostly a direct copy-paste of the code provided by the authors here:
  https://github.com/LiyuanLucasLiu/RAdam/blob/master/radam.py
class_docstr_tok: ["Implements","rectified","adam","as","derived","in","the","following","paper",":","''","On","the","Variance","of","the","Adaptive","Learning","Rate","and","Beyond","''","(","https",":","\/\/arxiv.org\/abs\/1908.03265",")","This","code","is","mostly","a","direct","copy-paste","of","the","code","provided","by","the","authors","here",":","https",":","\/\/github.com\/LiyuanLucasLiu\/RAdam\/blob\/master\/radam.py"]
code: def from_config(cls, config: Config, model: torch.nn.Module):
      return cls(
          model.parameters(),
          lr=config.lr,
          weight_decay=config.weight_decay,
          eps=config.eps,
      )
  
file_path: pytext/pytext/optimizer/radam.py
imports: import math
  import torch
  from pytext.optimizer.optimizers import Optimizer
  from torch.optim import Optimizer
label_desc: Use image node_id 4 for calling the RAdam obj's underlying member method code with example usage: obj.from_config(cls, config, model) and returns: cls