class_docstr: A learning rate decay policy, where the effective learning rate is
  calculated as base_lr * gamma ^ (floor(iter / step_size))
  
  
  :param step_size:
  :param gamma:
  
  
  >>> step = Step(2, 0.3)
  creating: createStep
code: def __init__(self, step_size, gamma):
      from bigdl.optim.optimizer import Step as BStep
  
      self.scheduler = BStep(step_size, gamma)
  
imports: from abc import ABC, abstractmethod
label_desc: Use image node_id 1 to create a new Step object from inherited base classes: Scheduler with example: obj = Step(step_size, gamma)