自己编写神经网络

import torch
from torch import nn
from torch.nn import Conv2d, MaxPool2d, Flatten, Linear, Sequential
from torch.utils.tensorboard import SummaryWriter


class Tudui(nn.Module):
    def __init__(self):
        super(Tudui, self).__init__()
        self.conv1=Conv2d(3,32,5,padding=2)
        self.maxpool1=MaxPool2d(2)  #2*2里面谁最大
        self.conv2=Conv2d(32,32,5,padding=2)
        self.maxpool2=MaxPool2d(2)  #2*2里面谁最大
        self.conv3=Conv2d(32,64,5,padding=2)
        self.maxpool3=MaxPool2d(2)  #2*2里面谁最大
        self.flatten = Flatten()
        self.liner1 = Linear(1024,64)
        self.liner2 = Linear(64,10)

        self.model1 = Sequential(
            Conv2d(3, 32, 5, padding=2),
            MaxPool2d(2),  # 2*2里面谁最大
            Conv2d(32, 32, 5, padding=2),
            MaxPool2d(2),  # 2*2里面谁最大
            Conv2d(32, 64, 5, padding=2),
            MaxPool2d(2),  # 2*2里面谁最大
            Flatten(),
            Linear(1024, 64),
            Linear(64, 10)
        )

    def forward(self,x):
        x=self.conv1(x)
        x =self.maxpool1(x)
        x = self.conv2(x)
        x = self.maxpool2(x)
        x = self.conv3(x)
        x = self.maxpool3(x)
        x= self.flatten(x)
        x= self.liner1(x)
        x=self.liner2(x)
        return x

tudui = Tudui()
input = torch.ones(64,3,32,32)
output = tudui(input)

#
# print(output)
# print(output.shape)
#
# print(tudui)

writer = SummaryWriter("圣经网络")
writer.add_graph(tudui,input)
writer.close()  #cmd输入    tensorboard --logdir=logs   logs改成绝对路径