PyTorch学习总结--完整训练

        训练过程中定义了损失函数，激活函数，优化器，并进行了测试，计算了测试准确率，并用tensorboard进行可视化，数据集采用torchvision的CIFAR10，并运用GPU训练

        🚀代码如下：

train.py

from torch import nn
import torch
import torchvision
from torch.nn import Conv2d, MaxPool2d, Flatten, Linear, ReLU
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter

from module import *

# 准备数据集
train_data = torchvision.datasets.CIFAR10(root='./dataset', train=True, transform=torchvision.transforms.ToTensor(),
                                          download=True)
val_data = torchvision.datasets.CIFAR10(root='./dataset', train=False, transform=torchvision.transforms.ToTensor(),
                                        download=True)

train_data_size = len(train_data)
val_data_size = len(val_data)

# 加载数据集
train_loader = DataLoader(train