def __init__(
      self,
      initial_learning_rate,
      decay_steps,
      decay_rate,
      staircase=False,
      name=None):
    """Applies exponential decay to the learning rate.

    Args:
      initial_learning_rate: A scalar `float32` or `float64` `Tensor` or a
        Python number.  The initial learning rate.
      decay_steps: A scalar `int32` or `int64` `Tensor` or a Python number.
        Must be positive.  See the decay computation above.
      decay_rate: A scalar `float32` or `float64` `Tensor` or a
        Python number.  The decay rate.
      staircase: Boolean.  If `True` decay the learning rate at discrete
        intervals
      name: String.  Optional name of the operation.  Defaults to
        'ExponentialDecay'.
    """
    super(ExponentialDecay, self).__init__()
    self.initial_learning_rate = initial_learning_rate
    self.decay_steps = decay_steps
    self.decay_rate = decay_rate
    self.staircase = staircase
    self.name = name