pytroch中计算网络权重参数的L1和L2

def l1_regularization(model, l1_alpha):
    l1_loss = []
    for module in model.modules():
        if type(module) is nn.BatchNorm2d:
            l1_loss.append(torch.abs(module.weight).sum())
    return l1_alpha * sum(l1_loss)

def l2_regularization(model, l2_alpha):
    l2_loss = []
    for module in model.modules():
        if type(module) is nn.Conv2d:
            l2_loss.append((module.weight ** 2).sum() / 2.0)
    return l2_alpha * sum(l2_loss)

原文链接：https://blog.csdn.net/hlld__/article/details/114276683