MultiStepLR
class torch.optim.lr_scheduler.MultiStepLR(optimizer, milestones, gamma=0.1, last_epoch=- 1, verbose=False)
Decays the learning rate of each parameter group by gamma once the
   number of epoch reaches one of the milestones. 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.
  * **milestones** (*list*) -- List of epoch indices. Must be
    increasing.

  * **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


