（刘二大人）PyTorch深度学习实践-卷积网络（基础篇作业）

1. 所实现的模型结构

 2.代码展示

import torch
import torchvision.datasets
from torchvision import transforms
from torch.utils.data import DataLoader
import torch.nn.functional as F
from torch.utils.tensorboard import SummaryWriter
 
#追踪日志
writer = SummaryWriter(log_dir='../LEDR')
#准备数据集
trans = transforms.Compose([transforms.ToTensor(),transforms.Normalize((0.1307,),(0.3801,))])
train_set = torchvision.datasets.MNIST(root='E:\learn_pytorch\LE',train=True,transform=trans,download=True)
test_set = torchvision.datasets.MNIST(root='E:\learn_pytorch\LE',train=False,transform=trans,download=True)
 
#加载数据集
train_data = DataLoader(dataset=train_set,batch_size=64,shuffle=True)
test_data = DataLoader(dataset=test_set,batch_size=64,shuf