lr_step function

Step learning rate decay

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.

lr_step(optimizer, step_size, gamma = 0.1, last_epoch = -1)

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()) {
## Not run:

# 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()
}
## End(Not run)

}