lmflow.optim.dummy

Dummy Optimizer.

Classes

Dummy

An dummy optimizer that does nothing.

Module Contents

class lmflow.optim.dummy.Dummy(params: collections.abc.Iterable[torch.nn.parameter.Parameter], lr: float = 0.0, betas: tuple[float, float] = (0.9, 0.999), weight_decay: float = 0.0)

Bases: torch.optim.Optimizer

An dummy optimizer that does nothing.

Parameters:

• params (Iterable[nn.parameter.Parameter]) – Iterable of parameters to optimize or dictionaries defining parameter groups.

• lr (float, optional, defaults to 0) – The learning rate to use.

step(closure: Callable = None)

Performs a single optimization step.

Parameters:

closure (Callable, optional) – A closure that reevaluates the model and returns the loss.