ConstantLR
class torch.optim.lr_scheduler.ConstantLR(optimizer, factor=0.3333333333333333, total_iters=5, last_epoch=- 1, verbose=False)
Decays the learning rate of each parameter group by a small
   constant factor until the number of epoch reaches a pre-defined
   milestone: total_iters. Notice that such decay can happen
   simultaneously with other changes to the learning rate from outside
   this scheduler. When last_epoch=-1, sets initial lr as lr.
Parameters:
      * optimizer (Optimizer) -- Wrapped optimizer.
  * **factor** (*float*) -- The number we multiply learning rate
    until the milestone. Default: 1./3.

  * **total_iters** (*int*) -- The number of steps that the
    scheduler decays the learning rate. Default: 5.

  * **last_epoch** (*int*) -- The index of the last epoch.
    Default: -1.

  * **verbose** (*bool*) -- If "True", prints a message to stdout
    for each update. Default: "False".

-[ Example ]-