MultiplicativeLR#
- class torch.optim.lr_scheduler.MultiplicativeLR(optimizer, lr_lambda, last_epoch=-1)[source]#
Multiply the learning rate of each parameter group by the factor given in the specified function.
When last_epoch=-1, set initial lr as lr.
- Parameters
Example
>>> lmbda = lambda epoch: 0.95 >>> scheduler = MultiplicativeLR(optimizer, lr_lambda=lmbda) >>> for epoch in range(100): >>> train(...) >>> validate(...) >>> scheduler.step()
- load_state_dict(state_dict)[source]#
Load the scheduler’s state.
- Parameters
state_dict (dict) – scheduler state. Should be an object returned from a call to
state_dict()
.