Source code for modulus.hydra.scheduler
"""
Supported PyTorch scheduler configs
"""
import torch
from dataclasses import dataclass
from hydra.core.config_store import ConfigStore
from omegaconf import MISSING
[docs]@dataclass
class SchedulerConf:
_target_ = MISSING
[docs]@dataclass
class ExponentialLRConf(SchedulerConf):
_target_: str = "torch.optim.lr_scheduler.ExponentialLR"
gamma: float = 0.99998718
[docs]@dataclass
class TFExponentialLRConf(SchedulerConf):
_target_: str = "custom"
_name_: str = "tf.ExponentialLR"
decay_rate: float = 0.95
decay_steps: int = 1000
[docs]@dataclass
class CosineAnnealingLRConf(SchedulerConf):
_target_: str = "torch.optim.lr_scheduler.CosineAnnealingLR"
T_max: int = 1000
eta_min: float = 0
last_epoch: int = -1
[docs]@dataclass
class CosineAnnealingWarmRestartsConf(SchedulerConf):
_target_: str = "torch.optim.lr_scheduler.CosineAnnealingWarmRestarts"
T_0: int = 1000
T_mult: int = 1
eta_min: float = 0
last_epoch: int = -1
[docs]def register_scheduler_configs() -> None:
cs = ConfigStore.instance()
cs.store(
group="scheduler",
name="exponential_lr",
node=ExponentialLRConf,
)
cs.store(
group="scheduler",
name="tf_exponential_lr",
node=TFExponentialLRConf,
)
cs.store(
group="scheduler",
name="cosine_annealing",
node=CosineAnnealingLRConf,
)
cs.store(
group="scheduler",
name="cosine_annealing_warm_restarts",
node=CosineAnnealingWarmRestartsConf,
)