jettify / pytorch-optimizer

Consider using f-strings PYL-C0209
Performance
Minor
4 occurrences in this check
Formatting a regular string which could be a f-string
 50            raise ValueError('Invalid dampening value: {}'.format(dampening))
 51        if weight_decay < 0.0:
 52            raise ValueError(
 53                'Invalid weight_decay value: {}'.format(weight_decay) 54            )
 55
 56        defaults = dict(
Formatting a regular string which could be a f-string
 47        if momentum < 0.0:
 48            raise ValueError('Invalid momentum value: {}'.format(momentum))
 49        if dampening < 0.0:
 50            raise ValueError('Invalid dampening value: {}'.format(dampening)) 51        if weight_decay < 0.0:
 52            raise ValueError(
 53                'Invalid weight_decay value: {}'.format(weight_decay)
Formatting a regular string which could be a f-string
 45        if lr <= 0.0:
 46            raise ValueError('Invalid learning rate: {}'.format(lr))
 47        if momentum < 0.0:
 48            raise ValueError('Invalid momentum value: {}'.format(momentum)) 49        if dampening < 0.0:
 50            raise ValueError('Invalid dampening value: {}'.format(dampening))
 51        if weight_decay < 0.0:
Formatting a regular string which could be a f-string
 43        nesterov: bool = False,
 44    ) -> None:
 45        if lr <= 0.0:
 46            raise ValueError('Invalid learning rate: {}'.format(lr)) 47        if momentum < 0.0:
 48            raise ValueError('Invalid momentum value: {}'.format(momentum))
 49        if dampening < 0.0: