class_docstr: [[Exponential]] is a learning rate schedule, which rescale the learning rate by
  lr_{n + 1} = lr * decayRate `^` (iter / decayStep)
  :param decay_step the inteval for lr decay
  :param decay_rate decay rate
  :param stair_case if true, iter / decayStep is an integer division
                   and the decayed learning rate follows a staircase function.
  
  >>> exponential = Exponential(100, 0.1)
  creating: createExponential
code: def __init__(self, decay_step, decay_rate, stair_case=False):
      from bigdl.optim.optimizer import Exponential as BExponential
  
      self.scheduler = BExponential(decay_step, decay_rate, stair_case)
  
imports: from abc import ABC, abstractmethod
label_desc: Use image node_id 1 to create a new Exponential object from inherited base classes: Scheduler with example: obj = Exponential(decay_step, decay_rate, stair_case)