Source code for draugr.torch_utilities.optimisation.scheduling.lr_scheduler
from bisect import bisect_right
__all__ = ["WarmupMultiStepLR"]
from torch.optim.lr_scheduler import _LRScheduler
[docs]class WarmupMultiStepLR(_LRScheduler):
"""description"""
[docs] def __init__(
self,
optimiser,
milestones,
gamma=0.1,
warmup_factor=1.0 / 3,
warmup_iters=500,
last_epoch=-1,
):
if not list(milestones) == sorted(milestones):
raise ValueError(
"Milestones should be a list of" " increasing integers. Got {}",
milestones,
)
self.milestones = milestones
self.gamma = gamma
self.warmup_factor = warmup_factor
self.warmup_iters = warmup_iters
super().__init__(optimiser, last_epoch)
[docs] def get_lr(self):
"""
:return:
:rtype:"""
warmup_factor = 1
if self.last_epoch < self.warmup_iters:
alpha = float(self.last_epoch) / self.warmup_iters
warmup_factor = self.warmup_factor * (1 - alpha) + alpha
return [
base_lr
* warmup_factor
* self.gamma ** bisect_right(self.milestones, self.last_epoch)
for base_lr in self.base_lrs
]