class_docstr: Vanilla Stochastic Gradient Descent.
  
  Args:
      lr (float): Learning rate.
class_docstr_tok: ["Vanilla","Stochastic","Gradient","Descent",".","Args",":","lr","(","float",")",":","Learning","rate","."]
code: def create_update_rule(self):
      return SGDRule(self.hyperparam)
  
file_path: chainer/chainer/optimizers/sgd.py
imports: from chainer.backends import cuda
  from chainer.backends import intel64
  from chainer import optimizer
  from chainer import types
label_desc: Use image node_id 2 for calling the SGD obj's underlying member method code with example usage: obj.create_update_rule() and returns: SGDRule