个人博客第一次提交，老天保佑千万别报错啊！！！

lion

再来个代码：

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
import torch
import torchvision
import torch.nn as nn
from torchsummary import summary

class Network(nn.Module):
    def __init__(self, input_size,output_size):
        super(Network,self).__init__()

        self.model = nn.Sequential(
            nn.Flatten(),
            nn.Linear(input_size,512),
            nn.BatchNorm1d(512),
            nn.ReLU(),

            nn.Linear(512,256),
            nn.BatchNorm1d(256),
            nn.Linear(256,128),
            nn.ReLU(),

            nn.BatchNorm1d(128),
            nn.ReLU(),
            nn.Linear(128,output_size)
        )

        for m in self.modules():
            if isinstance(m, nn.Linear):
                # 正态分布初始化
                nn.init.normal_(m.weight, 0, 0.01)
                if m.bias is not None:
                    nn.init.constant_(m.bias, 0)
    def forward(self,x):
        return self.model(x)
    
# if __name__ == "__main__":
#     network = Network(input_size=1*28*28,output_size=10)
#     # print(network)
#     torch.manual_seed(0)
#     # x = torch.randn((1,28,28))
#     # output = network(x)
#     summary(network,input_size=(1, 28, 28),batch_size=16,device="cpu")