class_docstr: Update rule for Nesterov's Accelerated Gradient.
  
  See :class:`~chainer.optimizers.NesterovAG` for the default values of the
  hyperparameters.
  
  Args:
      parent_hyperparam (~chainer.optimizer.Hyperparameter): Hyperparameter
          that provides the default values.
      lr (float): Learning rate.
      momentum (float): Exponential decay rate of the first order moment.
class_docstr_tok: ["Update","rule","for","Nesterov","'s","Accelerated","Gradient",".","See",":","class",":","`","~chainer.optimizers.NesterovAG","`","for","the","default","values","of","the","hyperparameters",".","Args",":","parent_hyperparam","(","~chainer.optimizer.Hyperparameter",")",":","Hyperparameter","that","provides","the","default","values",".","lr","(","float",")",":","Learning","rate",".","momentum","(","float",")",":","Exponential","decay","rate","of","the","first","order","moment","."]
code: def init_state(self, param):
      with chainer.using_device(param.device):
          xp = param.device.xp
          self.state["v"] = xp.zeros_like(param.data)
  
file_path: chainer/chainer/optimizers/nesterov_ag.py
imports: import chainer
  from chainer.backends import cuda
  from chainer import optimizer
  from chainer import types
label_desc: Use image node_id 2 for calling the NesterovAGRule obj's underlying member method code with example usage: obj.init_state(param) without return types