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()

Returns the state of the scheduler as a dict.

It contains an entry for every variable in self.__dict__ which is not the optimizer.