class_docstr: Update rule for the classical momentum SGD.
  
  See :class:`~chainer.optimizers.MomentumSGD` 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","classical","momentum","SGD",".","See",":","class",":","`","~chainer.optimizers.MomentumSGD","`","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, -self.hyperparam.lr, grad
          )
          param.data += v
      else:
          v *= self.hyperparam.momentum
          v -= self.hyperparam.lr * grad
          param.data += v
  
file_path: chainer/chainer/optimizers/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 MomentumSGDRule obj's underlying member method code with example usage: obj.update_core_cpu(param) without return types