Decays the learning rate of each parameter group by gamma every step_size epochs. Notice that such decay can happen simultaneously with other changes to the learning rate from outside this scheduler. When last_epoch=-1, sets initial lr as lr.
Arguments
- optimizer
(Optimizer): Wrapped optimizer.
- step_size
(int): Period of learning rate decay.
- gamma
(float): Multiplicative factor of learning rate decay. Default: 0.1.
- last_epoch
(int): The index of last epoch. Default: -1.
Examples
if (torch_is_installed()) {
if (FALSE) {
# Assuming optimizer uses lr = 0.05 for all groups
# lr = 0.05 if epoch < 30
# lr = 0.005 if 30 <= epoch < 60
# lr = 0.0005 if 60 <= epoch < 90
# ...
scheduler <- lr_step(optimizer, step_size = 30, gamma = 0.1)
for (epoch in 1:100) {
train(...)
validate(...)
scheduler$step()
}
}
}