多方法解决MNIST数字识别

全连接层

import torch
from torchvision import datasets, transforms
import torch.nn as nn
import torch.optim as optim
from tqdm import tqdm  # 用于进度条显示
import os# 定义数据预处理（标准化+Tensor转换）
transform = transforms.Compose([transforms.ToTensor(),transforms.Normalize((0.1307,), (0.3081,))  # MNIST的均值和标准差
])# 下载/加载数据集
train_dataset = datasets.MNIST(root='./data', train=True, download=True, transform=transform
)test_dataset = datasets.MNIST(root='./data', train=False, download=True, transform=transform
)# 创建DataLoader
train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=64, shuffle=True)
test_loader = torch.u