class_docstr: Update rule for the corrected momentum SGD.
  
  See :class:`~chainer.optimizers.CorrectedMomentumSGD` 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","the","corrected","momentum","SGD",".","See",":","class",":","`","~chainer.optimizers.CorrectedMomentumSGD","`","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 update_core_cpu(self, param):
      grad = param.grad
      if grad is None:
          return
      v = self.state["v"]
      if isinstance(v, intel64.mdarray):
          v.inplace_axpby(self.hyperparam.momentum, -1, grad)
          param.data += self.hyperparam.lr * v
      else:
          v *= self.hyperparam.momentum
          v -= grad
          param.data += self.hyperparam.lr * v
  
file_path: chainer/chainer/optimizers/corrected_momentum_sgd.py
imports: import chainer
  from chainer.backends import cuda
  from chainer.backends import intel64
  from chainer import optimizer
  from chainer import types
label_desc: Use image node_id 3 for calling the CorrectedMomentumSGDRule obj's underlying member method code with example usage: obj.update_core_cpu(param) without return types