class_docstr: Alex Graves's RMSprop.
  
  See: https://arxiv.org/abs/1308.0850
  
  Args:
      lr (float): Learning rate.
      alpha (float): Exponential decay rate of the first and second order
          moments of the raw gradient.
      momentum (float): Exponential decay rate of the first order moment of
          the adjusted gradient.
      eps (float): Small value for the numerical stability.
class_docstr_tok: ["Alex","Graves","'s","RMSprop",".","See",":","https",":","\/\/arxiv.org\/abs\/1308.0850","Args",":","lr","(","float",")",":","Learning","rate",".","alpha","(","float",")",":","Exponential","decay","rate","of","the","first","and","second","order","moments","of","the","raw","gradient",".","momentum","(","float",")",":","Exponential","decay","rate","of","the","first","order","moment","of","the","adjusted","gradient",".","eps","(","float",")",":","Small","value","for","the","numerical","stability","."]
code: def create_update_rule(self):
      return RMSpropGravesRule(self.hyperparam)
  
file_path: chainer/chainer/optimizers/rmsprop_graves.py
imports: import numpy
  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 RMSpropGraves obj's underlying member method code with example usage: obj.create_update_rule() and returns: RMSpropGravesRule