Method step

ML/src/python/neuralforge/optim/optimizers.py:250–259

(self, closure=None)

            fast_p.data.copy_(slow)
    
    def step(self, closure=None):
        loss = self.optimizer.step(closure)
        
        for group in self.param_groups:
            group['counter'] += 1
            if group['counter'] >= self.k:
                self.update(group)
                group['counter'] = 0
        
        return loss
    
    def state_dict(self):
        return {