code: def __init__(
      self,
      backend,
      multiplier,
      start_epoch=0,
      end_epoch=None,
      staircase=True,
      momentum_correction=True,
      steps_per_epoch=None,
      initial_lr=None,
      *args,
  ):
      super(LearningRateScheduleCallbackImpl, self).__init__(*args)
      self.backend = backend
      self.start_epoch = start_epoch
      self.end_epoch = end_epoch
      self.staircase = staircase
      self.momentum_correction = momentum_correction
      self.initial_lr = initial_lr
      self.restore_momentum = None
      self.steps_per_epoch = steps_per_epoch
      self.current_epoch = None
  
      if not callable(multiplier):
          self.staircase = True
          self.multiplier = lambda epoch: multiplier
      else:
          self.multiplier = multiplier
  
      if self.initial_lr is None:
          warnings.warn(
              "Parameter `initial_lr` will be required in the future",
              DeprecationWarning,
          )
  
imports: import warnings
  import byteps.tensorflow
  import tensorflow
label_desc: Use image node_id 1 to create a new LearningRateScheduleCallbackImpl object from inherited base classes: object with example: obj = LearningRateScheduleCallbackImpl(backend, multiplier, start_epoch, end_epoch, staircase, momentum_correction, steps_per_epoch, initial_lr)