code: def inverse_exp_decay(max_step, min_value=0.01, step=None):
    
    inv_base = tf.exp(tf.log(min_value) / float(max_step))
    if step is None:
      step = tf.train.get_global_step()
    if step is None:
      return 1.0
    step = to_float(step)
    return inv_base**tf.maximum(float(max_step) - step, 0.0)
docs: Inverse-decay exponentially from 0.01 to 1.0 reached at max_step.