Method __init__

bitsandbytes/optim/lars.py:171–198

(
        self,
        params,
        lr=0.01,
        momentum=0,
        dampening=0,
        weight_decay=0,
        nesterov=False,
        max_unorm=0.02,
    )

class PytorchLARS(Optimizer):
    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(f"Invalid learning rate: {lr}")
        if momentum < 0.0:
            raise ValueError(f"Invalid momentum value: {momentum}")
        if weight_decay < 0.0:
            raise ValueError(f"Invalid weight_decay value: {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().__init__(params, defaults)

    def __setstate__(self, state):
        super().__setstate__(state)