def _register_corrected_decay_optimizers()

in timm/optim/_optim_factory.py [0:0]

• 121 lines of code
• 3 McCabe index (conditional complexity)

def _register_corrected_decay_optimizers(registry: OptimizerRegistry) -> None:
    """Register corrected weight decay optimizer variants"""
    corrected_optimizers = [
        OptimInfo(
            name='adamc',
            opt_class=AdamWLegacy,
            description='AdamW with corrected weight decay (lr²/max_lr scaling)',
            has_betas=True,
            defaults={'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='nadamc',
            opt_class=NAdamW,
            description='NAdamW with corrected weight decay (lr²/max_lr scaling)',
            has_betas=True,
            defaults={'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='sgdc',
            opt_class=SGDW,
            description='SGD with corrected decoupled weight decay (lr²/max_lr scaling)',
            has_eps=False,
            has_momentum=True,
            defaults={'nesterov': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='adoptc',
            opt_class=Adopt,
            description='Adopt with corrected decoupled weight decay (lr²/max_lr scaling)',
            defaults={'decoupled': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='lambcd',
            opt_class=Lamb,
            description='LAMB with corrected decoupled weight decay (lr²/max_lr scaling)',
            has_betas=True,
            defaults={'decoupled_decay': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='kronc',
            opt_class=Kron,
            description='PSGD Kron with corrected decoupled weight decay (lr²/max_lr scaling)',
            has_momentum=True,
            defaults={'decoupled_decay': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='lionc',
            opt_class=Lion,
            description='Lion with corrected weight decay (lr²/max_lr scaling)',
            has_eps=False,
            has_betas=True,
            defaults={'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='lapropc',
            opt_class=LaProp,
            description='LaProp with corrected weight decay (lr²/max_lr scaling)',
            has_betas=True,
            defaults={'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='rmsproptfc',
            opt_class=RMSpropTF,
            description='RMSprop TF-style with corrected decoupled weight decay (lr²/max_lr scaling)',
            has_momentum=True,
            defaults={'alpha': 0.9, 'decoupled_decay': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='adafactorbvc',
            opt_class=AdafactorBigVision,
            description='Adafactor Big Vision with corrected weight decay (lr²/max_lr or lr/max_lr scaling)',
            defaults={'corrected_weight_decay': True}
        ),
    ]
    for opt in corrected_optimizers:
        registry.register(opt)

    # Cautious + corrected variants
    cautious_corrected = [
        OptimInfo(
            name='cadamc',
            opt_class=AdamWLegacy,
            description='Cautious AdamW with corrected weight decay (lr²/max_lr scaling)',
            has_betas=True,
            defaults={'caution': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='cadoptc',
            opt_class=Adopt,
            description='Cautious Adopt with corrected decoupled weight decay (lr²/max_lr scaling)',
            defaults={'decoupled': True, 'caution': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='cnadamc',
            opt_class=NAdamW,
            description='Cautious NAdamW with corrected weight decay (lr²/max_lr scaling)',
            has_betas=True,
            defaults={'caution': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='csgdc',
            opt_class=SGDW,
            description='Cautious SGD with corrected decoupled weight decay (lr²/max_lr scaling)',
            has_eps=False,
            has_momentum=True,
            defaults={'nesterov': True, 'caution': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='clionc',
            opt_class=Lion,
            description='Cautious Lion with corrected weight decay (lr²/max_lr scaling)',
            has_eps=False,
            has_betas=True,
            defaults={'caution': True, 'corrected_weight_decay': True}
        ),
        OptimInfo(
            name='cadafactorbvc',
            opt_class=AdafactorBigVision,
            description='Cautious Adafactor Big Vision with corrected weight decay',
            defaults={'caution': True, 'corrected_weight_decay': True}
        ),
    ]
    for opt in cautious_corrected:
        registry.register(opt)