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ExponentialLR
class torch.optim.lr_scheduler.ExponentialLR(optimizer, gamma, last_epoch=-1, verbose=False)
[source]-
Decays the learning rate of each parameter group by gamma every epoch. When last_epoch=-1, sets initial lr as lr.
- Parameters
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()
-
Returns the state of the scheduler as a
dict
.It contains an entry for every variable in self.__dict__ which is not the optimizer.
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https://pytorch.org/docs/2.1/generated/torch.optim.lr_scheduler.ExponentialLR.html