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92 lines
3.0 KiB
92 lines
3.0 KiB
""" Scheduler Factory
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Hacked together by / Copyright 2020 Ross Wightman
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"""
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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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from .multistep_lr import MultiStepLRScheduler
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def create_scheduler(args, optimizer):
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num_epochs = args.epochs
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if getattr(args, 'lr_noise', None) is not None:
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lr_noise = getattr(args, 'lr_noise')
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if isinstance(lr_noise, (list, tuple)):
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noise_range = [n * num_epochs for n in lr_noise]
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if len(noise_range) == 1:
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noise_range = noise_range[0]
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else:
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noise_range = lr_noise * num_epochs
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else:
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noise_range = None
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noise_args = dict(
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noise_range_t=noise_range,
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noise_pct=getattr(args, 'lr_noise_pct', 0.67),
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noise_std=getattr(args, 'lr_noise_std', 1.),
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noise_seed=getattr(args, 'seed', 42),
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)
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lr_scheduler = None
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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=getattr(args, 'lr_cycle_mul', 1.),
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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=getattr(args, 'lr_cycle_limit', 1),
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t_in_epochs=True,
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**noise_args,
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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=getattr(args, 'lr_cycle_mul', 1.),
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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=getattr(args, 'lr_cycle_limit', 1),
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t_in_epochs=True,
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**noise_args,
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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_args,
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)
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elif args.sched == 'multistep':
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lr_scheduler = MultiStepLRScheduler(
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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_args,
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)
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elif args.sched == 'plateau':
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mode = 'min' if 'loss' in getattr(args, 'eval_metric', '') else 'max'
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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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mode=mode,
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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=0,
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**noise_args,
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)
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return lr_scheduler, num_epochs
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