You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
85 lines
3.1 KiB
85 lines
3.1 KiB
from .cosine_lr import CosineLRScheduler
|
|
from .tanh_lr import TanhLRScheduler
|
|
from .step_lr import StepLRScheduler
|
|
from .plateau_lr import PlateauLRScheduler
|
|
|
|
|
|
def create_scheduler(args, optimizer):
|
|
num_epochs = args.epochs
|
|
|
|
if getattr(args, 'lr_noise', None) is not None:
|
|
lr_noise = getattr(args, 'lr_noise')
|
|
if isinstance(lr_noise, (list, tuple)):
|
|
noise_range = [n * num_epochs for n in lr_noise]
|
|
if len(noise_range) == 1:
|
|
noise_range = noise_range[0]
|
|
else:
|
|
noise_range = lr_noise * num_epochs
|
|
else:
|
|
noise_range = None
|
|
|
|
lr_scheduler = None
|
|
if args.sched == 'cosine':
|
|
lr_scheduler = CosineLRScheduler(
|
|
optimizer,
|
|
t_initial=num_epochs,
|
|
t_mul=getattr(args, 'lr_cycle_mul', 1.),
|
|
lr_min=args.min_lr,
|
|
decay_rate=args.decay_rate,
|
|
warmup_lr_init=args.warmup_lr,
|
|
warmup_t=args.warmup_epochs,
|
|
cycle_limit=getattr(args, 'lr_cycle_limit', 1),
|
|
t_in_epochs=True,
|
|
noise_range_t=noise_range,
|
|
noise_pct=getattr(args, 'lr_noise_pct', 0.67),
|
|
noise_std=getattr(args, 'lr_noise_std', 1.),
|
|
noise_seed=getattr(args, 'seed', 42),
|
|
)
|
|
num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs
|
|
elif args.sched == 'tanh':
|
|
lr_scheduler = TanhLRScheduler(
|
|
optimizer,
|
|
t_initial=num_epochs,
|
|
t_mul=getattr(args, 'lr_cycle_mul', 1.),
|
|
lr_min=args.min_lr,
|
|
warmup_lr_init=args.warmup_lr,
|
|
warmup_t=args.warmup_epochs,
|
|
cycle_limit=getattr(args, 'lr_cycle_limit', 1),
|
|
t_in_epochs=True,
|
|
noise_range_t=noise_range,
|
|
noise_pct=getattr(args, 'lr_noise_pct', 0.67),
|
|
noise_std=getattr(args, 'lr_noise_std', 1.),
|
|
noise_seed=getattr(args, 'seed', 42),
|
|
)
|
|
num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs
|
|
elif args.sched == 'step':
|
|
lr_scheduler = StepLRScheduler(
|
|
optimizer,
|
|
decay_t=args.decay_epochs,
|
|
decay_rate=args.decay_rate,
|
|
warmup_lr_init=args.warmup_lr,
|
|
warmup_t=args.warmup_epochs,
|
|
noise_range_t=noise_range,
|
|
noise_pct=getattr(args, 'lr_noise_pct', 0.67),
|
|
noise_std=getattr(args, 'lr_noise_std', 1.),
|
|
noise_seed=getattr(args, 'seed', 42),
|
|
)
|
|
elif args.sched == 'plateau':
|
|
mode = 'min' if 'loss' in getattr(args, 'eval_metric', '') else 'max'
|
|
lr_scheduler = PlateauLRScheduler(
|
|
optimizer,
|
|
decay_rate=args.decay_rate,
|
|
patience_t=args.patience_epochs,
|
|
lr_min=args.min_lr,
|
|
mode=mode,
|
|
warmup_lr_init=args.warmup_lr,
|
|
warmup_t=args.warmup_epochs,
|
|
cooldown_t=0,
|
|
noise_range_t=noise_range,
|
|
noise_pct=getattr(args, 'lr_noise_pct', 0.67),
|
|
noise_std=getattr(args, 'lr_noise_std', 1.),
|
|
noise_seed=getattr(args, 'seed', 42),
|
|
)
|
|
|
|
return lr_scheduler, num_epochs
|