class_docstr: ExponentialScheduler
  Exponential decay
class_docstr_tok: ["ExponentialScheduler","Exponential","decay"]
docstr: Args:
      init_lr (float): Initial learning rate.
      gamma (float): Multiplier.
      iter_interval (int): Period of iteration at which gamma is multiplied.
          The default is 1.
docstr_tok: ["Args",":","init_lr","(","float",")",":","Initial","learning","rate",".","gamma","(","float",")",":","Multiplier",".","iter_interval","(","int",")",":","Period","of","iteration","at","which","gamma","is","multiplied",".","The","default","is","1","."]
code: def __init__(self, init_lr, gamma, iter_interval=1):
      """
      Args:
          init_lr (float): Initial learning rate.
          gamma (float): Multiplier.
          iter_interval (int): Period of iteration at which gamma is multiplied.
              The default is 1.
      """
      self.init_lr = init_lr
      self.gamma = gamma
      self.iter_interval = iter_interval
  
imports: import math
label_desc: Use image node_id 1 to create a new ExponentialScheduler object from inherited base classes: BaseLearningRateScheduler with example: obj = ExponentialScheduler(init_lr, gamma, iter_interval)