class_docstr: Implements stochastic gradient descent warm (optionally with momentum).
  
  It has been proposed in `Fixing Weight Decay Regularization in Adam <https://arxiv.org/abs/1711.05101>`_.
  
  Nesterov momentum is based on the formula from
  `On the importance of initialization and momentum in deep learning <http://www.cs.toronto.edu/%7Ehinton/absps/momentum.pdf>`_.
  
  :param params (iterable): iterable of parameters to optimize or dicts defining parameter groups
  :param lr: (float): learning rate
  :param momentum: (float, optional): momentum factor (default: 0)
  :param weight_decay: (float, optional): weight decay (L2 penalty) (default: 0)
  :param dampening: (float, optional): dampening for momentum (default: 0)
  :param nesterov: (bool, optional): enables Nesterov momentum (default: False)
  
  Example:
      >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
      >>> optimizer.zero_grad()
      >>> loss_fn(model(input_), target).backward()
      >>> optimizer.step()
  
  .. note::
      The implementation of SGD with Momentum/Nesterov subtly differs from
      Sutskever et. al. and implementations in some other frameworks.
  
      Considering the specific case of Momentum, the update can be written as
  
      .. math::
                v = \rho * v + g \\
                p = p - lr * v
  
      where p, g, v and :math:`\rho` denote the parameters, gradient,
      velocity, and momentum respectively.
  
      This is in contrast to Sutskever et. al. and
      other frameworks which employ an update of the form
  
      .. math::
           v = \rho * v + lr * g \\
           p = p - v
  
      The Nesterov version is analogously modified.
code: def __setstate__(self, state):
      super(SGD, self).__setstate__(state)
      for group in self.param_groups:
          group.setdefault("nesterov", False)
  
imports: import torch
  from torch.optim.optimizer import Optimizer
  from torch.optim import SGD
label_desc: Use image node_id 2 for calling the SGDW obj's underlying member method code with example usage: obj.__setstate__(state) without return types