def step(self, closure: Optional[Callable] = None):
        """Perform no-op optimization step where no parameters are updated.

        Args:
            closure (Callable, optional): A closure that reevaluates the model
                and returns the loss.
        """
        loss = None
        if closure is not None:
            with torch.enable_grad():
                loss = closure()

        return loss
Perform no-op optimization step where no parameters are updated.

        Args:
            closure (Callable, optional): A closure that reevaluates the model
                and returns the loss.
        
llmfoundry/optim/no_op.py