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78 lines
2.5 KiB
78 lines
2.5 KiB
from .cosine_lr import CosineLRScheduler
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from .tanh_lr import TanhLRScheduler
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from .step_lr import StepLRScheduler
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from .plateau_lr import PlateauLRScheduler
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def create_scheduler(args, optimizer):
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num_epochs = args.epochs
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if args.lr_noise is not None:
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if isinstance(args.lr_noise, (list, tuple)):
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noise_range = [n * num_epochs for n in args.lr_noise]
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else:
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noise_range = args.lr_noise * num_epochs
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print('Noise range:', noise_range)
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else:
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noise_range = None
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lr_scheduler = None
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#FIXME expose cycle parms of the scheduler config to arguments
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if args.sched == 'cosine':
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lr_scheduler = CosineLRScheduler(
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optimizer,
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t_initial=num_epochs,
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t_mul=1.0,
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lr_min=args.min_lr,
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decay_rate=args.decay_rate,
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warmup_lr_init=args.warmup_lr,
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warmup_t=args.warmup_epochs,
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cycle_limit=1,
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t_in_epochs=True,
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noise_range_t=noise_range,
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noise_pct=args.lr_noise_pct,
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noise_std=args.lr_noise_std,
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noise_seed=args.seed,
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)
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num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs
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elif args.sched == 'tanh':
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lr_scheduler = TanhLRScheduler(
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optimizer,
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t_initial=num_epochs,
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t_mul=1.0,
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lr_min=args.min_lr,
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warmup_lr_init=args.warmup_lr,
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warmup_t=args.warmup_epochs,
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cycle_limit=1,
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t_in_epochs=True,
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noise_range_t=noise_range,
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noise_pct=args.lr_noise_pct,
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noise_std=args.lr_noise_std,
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noise_seed=args.seed,
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)
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num_epochs = lr_scheduler.get_cycle_length() + args.cooldown_epochs
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elif args.sched == 'step':
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lr_scheduler = StepLRScheduler(
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optimizer,
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decay_t=args.decay_epochs,
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decay_rate=args.decay_rate,
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warmup_lr_init=args.warmup_lr,
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warmup_t=args.warmup_epochs,
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noise_range_t=noise_range,
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noise_pct=args.lr_noise_pct,
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noise_std=args.lr_noise_std,
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noise_seed=args.seed,
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)
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elif args.sched == 'plateau':
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lr_scheduler = PlateauLRScheduler(
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optimizer,
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decay_rate=args.decay_rate,
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patience_t=args.patience_epochs,
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lr_min=args.min_lr,
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warmup_lr_init=args.warmup_lr,
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warmup_t=args.warmup_epochs,
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cooldown_t=args.cooldown_epochs,
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)
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return lr_scheduler, num_epochs
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