class_docstr: `AdaBelief Optimizer, adapting stepsizes by the belief in observed gradients`
  Paper: https://arxiv.org/abs/2010.07468
  Implementation has been copied over from the original author (https://github.com/juntang-zhuang/Adabelief-Optimizer)
class_docstr_tok: ["`","AdaBelief","Optimizer",",","adapting","stepsizes","by","the","belief","in","observed","gradients","`","Paper",":","https",":","\/\/arxiv.org\/abs\/2010.07468","Implementation","has","been","copied","over","from","the","original","author","(","https",":","\/\/github.com\/juntang-zhuang\/Adabelief-Optimizer",")"]
code: def __setstate__(self, state):
      super(AdaBelief, self).__setstate__(state)
      for group in self.param_groups:
          group.setdefault("amsgrad", False)
  
file_path: pytext/pytext/optimizer/adabelief.py
imports: import math
  import torch
  from torch.optim.optimizer import Optimizer
  from .optimizers import Optimizer
label_desc: Use image node_id 3 for calling the AdaBelief obj's underlying member method code with example usage: obj.__setstate__(state) without return types