rate; at the start of a cycle, momentum is 'max_momentum' and
        learning rate is 'base_lr' Default: 0.9
  * **last_epoch** (*int*) -- The index of the last batch. This
    parameter is used when resuming a training job. Since *step()*
    should be invoked after each batch instead of after each
    epoch, this number represents the total number of *batches*
    computed, not the total number of epochs computed. When
    last_epoch=-1, the schedule is started from the beginning.
    Default: -1

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

-[ Example ]-



optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
scheduler = torch.optim.lr_scheduler.CyclicLR(optimizer, base_lr=0.01, max_lr=0.1)
data_loader = torch.utils.data.DataLoader(...)
for epoch in range(10):
    for batch in data_loader:
        train_batch(...)


