amplitude by half each cycle.

"exp_range": A cycle that scales initial amplitude by
     \text{gamma}^{\text{cycle iterations}} at each cycle iteration.

This implementation was adapted from the github repo:
   bckenstler/CLR
Parameters:
      * optimizer (Optimizer) -- Wrapped optimizer.
  * **base_lr** (*float** or **list*) -- Initial learning rate
    which is the lower boundary in the cycle for each parameter
    group.

  * **max_lr** (*float** or **list*) -- Upper learning rate
    boundaries in the cycle for each parameter group.
    Functionally, it defines the cycle amplitude (max_lr -
    base_lr). The lr at any cycle is the sum of base_lr and some
    scaling of the amplitude; therefore max_lr may not actually be
    reached depending on scaling function.

  * **step_size_up** (*int*) -- Number of training iterations in
    the increasing half of a cycle. Default: 2000
