helios.scheduler.utils¶
Attributes¶
Global instance of the registry for schedulers. |
Functions¶
|
Create the scheduler for the given type. |
Module Contents¶
- helios.scheduler.utils.SCHEDULER_REGISTRY¶
Global instance of the registry for schedulers.
By default, the registry contains the following schedulers:
¶ Scheduler
Name
torch.optim.lr_scheduler.LambdaLR
LambdaLR
torch.optim.lr_scheduler.MultiplicativeLR
MultiplicativeLR
torch.optim.lr_scheduler.StepLR
StepLR
torch.optim.lr_scheduler.MultiStepLR
MultiStepLR
torch.optim.lr_scheduler.ConstantLR
ConstantLR
torch.optim.lr_scheduler.LinearLR
LinearLR
torch.optim.lr_scheduler.ExponentialLR
ExponentialLR
torch.optim.lr_scheduler.PolynomialLR
PolynomialLR
torch.optim.lr_scheduler.CosineAnnealingLR
CosineAnnealingLR
torch.optim.lr_scheduler.SequentialLR
SequentialLR
torch.optim.lr_scheduler.ReduceLROnPlateau
ReduceLROnPlateau
torch.optim.lr_scheduler.CyclicLR
CyclicLR
torch.optim.lr_scheduler.OneCycleLR
OneCycleLR
torch.optim.lr_scheduler.CosineAnnealingWarmRestarts
CosineAnnealingWarmRestarts
CosineAnnealingRestartLR
MultiStepRestartLR
Example
import helios.optim as hlo import helios.scheduler as hls # This automatically registers your optimizer. @hls.SCHEDULER_REGISTRY.register class MyScheduler: ... # Alternatively you can manually register a scheduler. like this: hls.SCHEDULER_REGISTRY.register(MyScheduler)
- helios.scheduler.utils.create_scheduler(type_name: str, *args: Any, **kwargs: Any) torch.nn.Module [source]¶
Create the scheduler for the given type.
- Parameters:
type_name – the type of the scheduler to create.
args – positional arguments to pass into the scheduler.
kwargs – keyword arguments to pass into the scheduler.
- Returns:
The scheduler.