towhee.trainer.scheduler.configure_constant_scheduler¶
- towhee.trainer.scheduler.configure_constant_scheduler(optimizer: Optimizer, last_epoch: int = -1)[source]¶
Return a scheduler with a constant learning rate, using the learning rate set in optimizer.
- Parameters:
optimizer (Optimizer) – The optimizer for which to schedule the learning rate.
last_epoch (int) – The last epoch when resuming training.
- Return (LambdaLR):
A constant scheduler
Example
>>> from towhee.trainer.scheduler import configure_constant_scheduler >>> from towhee.trainer.optimization.adamw import AdamW >>> from torch import nn >>> def unwrap_scheduler(scheduler, num_steps=10): >>> lr_sch = [] >>> for _ in range(num_steps): >>> lr_sch.append(scheduler.get_lr()[0]) >>> scheduler.step() >>> return lr_sch >>> mdl = nn.Linear(50, 50) >>> optimizer = AdamW(mdl.parameters(), lr=10.0) >>> num_steps = 2 >>> scheduler = configure_constant_scheduler(optimizer) >>> lr_sch_1 = unwrap_scheduler(scheduler, num_steps) [10.0, 10.0]