def _register_cautious_optimizers()

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

• 110 lines of code
• 2 McCabe index (conditional complexity)

def _register_cautious_optimizers(registry: OptimizerRegistry) -> None:
    cautious_optimizers = [
        OptimInfo(
            name='cadafactor',
            opt_class=Adafactor,
            description='Cautious Adafactor',
            defaults={'caution': True}
        ),
        OptimInfo(
            name='cadafactorbv',
            opt_class=AdafactorBigVision,
            description='Cautious Big Vision Adafactor',
            defaults={'caution': True}
        ),
        OptimInfo(
            name='cadamw',
            opt_class=AdamWLegacy,
            description='Cautious AdamW',
            has_betas=True,
            defaults={'caution': True}
        ),
        OptimInfo(
            name='cadopt',
            opt_class=Adopt,
            description='Cautious Adopt',
            defaults={'caution': True}
        ),
        OptimInfo(
            name='cadan',
            opt_class=Adan,
            description='Cautious Adaptive Nesterov Momentum Algorithm',
            defaults={'caution': True, 'no_prox': False},
            has_betas=True,
            num_betas=3
        ),
        OptimInfo(
            name='cadanw',
            opt_class=Adan,
            description='Cautious Adaptive Nesterov Momentum with decoupled weight decay',
            defaults={'caution': True, 'no_prox': True},
            has_betas=True,
            num_betas=3
        ),
        OptimInfo(
            name='cadoptw',
            opt_class=Adopt,
            description='Cautious AdoptW (decoupled decay)',
            defaults={'decoupled': True, 'caution': True}
        ),
        OptimInfo(
            name='clamb',
            opt_class=Lamb,
            description='Cautious LAMB',
            has_betas=True,
            defaults={'caution': True}
        ),
        OptimInfo(
            name='clambw',
            opt_class=Lamb,
            description='Cautious LAMB with decoupled weight decay',
            has_betas=True,
            defaults={'caution': True, 'decoupled_decay': True}
        ),
        OptimInfo(
            name='claprop',
            opt_class=LaProp,
            description='Cautious LaProp',
            has_betas=True,
            defaults={'caution': True}
        ),
        OptimInfo(
            name='clion',
            opt_class=Lion,
            description='Cautious Lion',
            has_eps=False,
            has_betas=True,
            defaults = {'caution': True}
        ),
        OptimInfo(
            name='cmars',
            opt_class=Mars,
            description='Cautious MARS',
            has_betas=True,
            defaults={'caution': True}
        ),
        OptimInfo(
            name='cnadamw',
            opt_class=NAdamW,
            description='Cautious NAdamW',
            has_betas=True,
            defaults={'caution': True}
        ),
        OptimInfo(
            name='crmsproptf',
            opt_class=RMSpropTF,
            description='Cautious TensorFlow-style RMSprop',
            has_momentum=True,
            defaults={'alpha': 0.9, 'caution': True}
        ),
        OptimInfo(
            name='csgdw',
            opt_class=SGDW,
            description='Cautious SGD with decoupled weight decay and Nesterov momentum',
            has_eps=False,
            has_momentum=True,
            defaults={'nesterov': True, 'caution': True}
        ),
    ]
    for opt in cautious_optimizers:
        registry.register(opt)