class_docstr: `MADGRAD Optimizer`: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic
  Optimization.
  Paper: https://arxiv.org/abs/2101.11075
  
  Implementation has been copied over from the original author
  (https://github.com/facebookresearch/madgrad/blob/master/madgrad/madgrad.py)
class_docstr_tok: ["`","MADGRAD","Optimizer","`",":","A","Momentumized",",","Adaptive",",","Dual","Averaged","Gradient","Method","for","Stochastic","Optimization",".","Paper",":","https",":","\/\/arxiv.org\/abs\/2101.11075","Implementation","has","been","copied","over","from","the","original","author","(","https",":","\/\/github.com\/facebookresearch\/madgrad\/blob\/master\/madgrad\/madgrad.py",")"]
docstr: Add a param group to the :class:`Optimizer` s `param_groups`.
  
  This can be useful when fine tuning a pre-trained network as frozen
  layers can be made trainable and added to the :class:`Optimizer` as
  training progresses.
  
  Args:
      param_group (dict): Specifies what Tensors should be optimized along
      with group specific optimization options.
docstr_tok: ["Add","a","param","group","to","the",":","class",":","`","Optimizer","`","s","`","param_groups","`",".","This","can","be","useful","when","fine","tuning","a","pre-trained","network","as","frozen","layers","can","be","made","trainable","and","added","to","the",":","class",":","`","Optimizer","`","as","training","progresses",".","Args",":","param_group","(","dict",")",":","Specifies","what","Tensors","should","be","optimized","along","with","group","specific","optimization","options","."]
code: def add_param_group(self, param_group):
      r"""Add a param group to the :class:`Optimizer` s `param_groups`.
  
      This can be useful when fine tuning a pre-trained network as frozen
      layers can be made trainable and added to the :class:`Optimizer` as
      training progresses.
  
      Args:
          param_group (dict): Specifies what Tensors should be optimized along
          with group specific optimization options.
      """
      super().add_param_group(param_group)
      self.initialize_state()
  
file_path: pytext/pytext/optimizer/madgrad.py
imports: import math
  from collections import defaultdict
  from typing import Optional
  import torch
  from torch.optim.optimizer import Optimizer
  from .optimizers import Optimizer
label_desc: Use image node_id 7 for calling the MADGRAD obj's underlying member method code with example usage: obj.add_param_group(param_group) without return types