ExponentialLR
class torch.optim.lr_scheduler.ExponentialLR(optimizer, gamma, last_epoch=- 1, verbose=False)
Decays the learning rate of each parameter group by gamma every
   epoch. When last_epoch=-1, sets initial lr as lr.
Parameters:
      * optimizer (Optimizer) -- Wrapped optimizer.
  * **gamma** (*float*) -- Multiplicative factor of learning rate
    decay.

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

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

get_last_lr()
  Return last computed learning rate by current scheduler.

load_state_dict(state_dict)
  Loads the schedulers state.

  Parameters:
     **state_dict** (*dict*) -- scheduler state. Should be an
     object returned from a call to "state_dict()".

print_lr(is_verbose, group, lr, epoch=None)
  Display the current learning rate.

state_dict()