def __init__()

in bitsandbytes/optim/lars.py [0:0]


    def __init__(self, params, lr=0.01, momentum=0, dampening=0,
                 weight_decay=0, nesterov=False, max_unorm=0.02):
        if lr < 0.0:
            raise ValueError("Invalid learning rate: {}".format(lr))
        if momentum < 0.0:
            raise ValueError("Invalid momentum value: {}".format(momentum))
        if weight_decay < 0.0:
            raise ValueError("Invalid weight_decay value: {}".format(weight_decay))

        defaults = dict(lr=lr, momentum=momentum, dampening=dampening,
                        weight_decay=weight_decay, nesterov=nesterov, max_unorm=max_unorm)
        if nesterov and (momentum <= 0 or dampening != 0):
            raise ValueError("Nesterov momentum requires a momentum and zero dampening")
        super(PytorchLARS, self).__init__(params, defaults)