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 = Default()
  creating: createDefault
code: def __init__(self) -> None:
      from bigdl.dllib.optim.optimizer import Default as BDefault
  
      self.scheduler = BDefault()
  
imports: from abc import ABC, abstractmethod
  from typing import List, Optional, TYPE_CHECKING
label_desc: Use image node_id 1 to create a new Default object from inherited base classes: Scheduler with example: obj = Default()