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a5f697619c
Summary: Some interfaces of schedulers defined in lr_scheduler.py are missing in lr_scheduler.pyi. Pull Request resolved: https://github.com/pytorch/pytorch/pull/23934 Differential Revision: D16726622 Pulled By: ezyang fbshipit-source-id: 45fd2d28fbb658c71f6fcd33b8997d6ee8e2b17d
40 lines
2.1 KiB
Python
40 lines
2.1 KiB
Python
from typing import Iterable, Any, Optional, Callable
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from .optimizer import Optimizer
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class _LRScheduler:
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def __init__(self, optimizer: Optimizer, last_epoch: int=...) -> None: ...
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def state_dict(self) -> dict: ...
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def load_state_dict(self, state_dict: dict) -> None: ...
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def get_lr(self) -> float: ...
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def step(self, epoch: int) -> None: ...
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class LambdaLR(_LRScheduler):
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def __init__(self, optimizer: Optimizer, lr_lambda: float, last_epoch: int=...) -> None: ...
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class StepLR(_LRScheduler):
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def __init__(self, optimizer: Optimizer, step_size: int, gamma: float=..., last_epoch: int=...) -> None:...
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class MultiStepLR(_LRScheduler):
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def __init__(self, optimizer: Optimizer, milestones: Iterable[int], gamma: float=..., last_epoch: int=...) -> None: ...
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class ExponentialLR(_LRScheduler):
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def __init__(self, optimizer: Optimizer, gamma: float, last_epoch: int=...) -> None: ...
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class CosineAnnealingLR(_LRScheduler):
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def __init__(self, optimizer: Optimizer, T_max: int, eta_min: float, last_epoch: int=...) -> None: ...
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class ReduceLROnPlateau:
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in_cooldown: bool
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def __init__(self, optimizer: Optimizer, mode: str=..., factor: float=..., patience: int=..., verbose: bool=..., threshold: float=..., threshold_mode: str=..., cooldown: int=..., min_lr: float=..., eps: float=...) -> None: ...
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def step(self, metrics: Any, epoch: Optional[int]=...) -> None: ...
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def state_dict(self) -> dict: ...
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def load_state_dict(self, state_dict: dict): ...
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class CyclicLR(_LRScheduler):
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def __init__(self, optimizer: Optimizer, base_lr: float=..., max_lr: float=..., step_size_up: int=..., step_size_down: int=..., mode: str=..., gamma: float=..., scale_fn: Optional[Callable[[float], float]]=..., scale_mode: str=..., cycle_momentum: bool=..., base_momentum: float=..., max_momentum: float=..., last_epoch: int=...) -> None: ...
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class CosineAnnealingWarmRestarts(_LRScheduler):
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def __init__(self, optimizer: Optimizer, T_0: int=..., T_mult: int=..., eta_min: int=..., last_epoch: int=...) -> None: ...
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def step(self, epoch: Optional[int] = ...) -> None: ...
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