StepLR
class torch.optim.lr_scheduler.StepLR(optimizer, step_size, gamma=0.1, last_epoch=- 1, verbose=False)
Decays the learning rate of each parameter group by gamma every
   step_size epochs. 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.
  * **step_size** (*int*) -- Period of learning rate decay.

  * **gamma** (*float*) -- Multiplicative factor of learning rate
    decay. Default: 0.1.

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

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

-[ Example ]-



Assuming optimizer uses lr = 0.05 for all groups
lr = 0.05     if epoch < 30
lr = 0.005    if 30 <= epoch < 60
lr = 0.0005   if 60 <= epoch < 90
...


