浅谈pytorch中的nn.Sequential(*net[3: 5])是啥意思

1 class ResNeXt101(nn.Module):
    2 def __init__(self):
        3 super(ResNeXt101, self).__init__()
        4 net = resnext101()
        # print(os.getcwd(), net)

        5 net = list(net.children())  # net.children()得到resneXt 的表层网络
        # for i, value in enumerate(net):
        #     print(i, value)
        6 self.layer0 = nn.Sequential(net[:3])  # 将前三层打包0， 1， 2两层
        print(self.layer0)
        7 self.layer1 = nn.Sequential(*net[3: 5])  # 将3, 4两层打包
        8 self.layer2 = net[5]
        9 self.layer3 = net[6]

net = list(net.children())

list1 = ["conv", ("relu", "maxing"), ("relu", "maxing", 3), 3]
list2 = [list1[:1]]
list3 = [*list1[:1]]
print("list2:{}, *list1[:2]:{}".format(list1[:1], *list1[:1]))