class_docstr: An implementation of RMSprop
  :param learningrate learning rate
  :param learningrate_decay learning rate decay
  :param decayrate decay rate, also called rho
  :param epsilon for numerical stability
  >>> adagrad = RMSprop()
  creating: createRMSprop
code: def __init__(
      self,
      learningrate=1e-2,
      learningrate_decay=0.0,
      decayrate=0.99,
      epsilon=1e-8,
  ):
      from bigdl.optim.optimizer import RMSprop as BRMSprop
  
      self.optimizer = BRMSprop(
          learningrate,
          learningrate_decay,
          decayrate,
          epsilon,
          bigdl_type="float",
      )
  
imports: from abc import ABC, abstractmethod
  from bigdl.util.common import DOUBLEMAX
  from zoo.orca.learn.optimizers.schedule import Scheduler
label_desc: Use image node_id 1 to create a new RMSprop object from inherited base classes: Optimizer with example: obj = RMSprop(learningrate, learningrate_decay, decayrate, epsilon)