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 __init__(self, lr=_default_hyperparam.lr):
      super(SGD, self).__init__()
      self.hyperparam.lr = lr
  
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 1 to create a new SGD object from inherited base classes: optimizer with example: obj = SGD(lr)