CIFAR-10 图片识别

"""
Copyright 2022 The TBAALi Authors. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

"""
 @Author: TBAALi
 @Email: jiaxx903@foxmail.com
 @FileName: CIFAR-10-Classfication.py
 @DateTime: 5/19/22 9:48 PM
 @SoftWare: PyCharm
 @Copyright: Copyright (C) 2022 TBAALi
"""

# CIFAR-10 数据集由 10 个类的 60000 个 32 X 32 彩色图像组成，
# 每个类由 6000 个图像，有 50000 个训练图像和 10000 个测试图像

# 导入数据及下载数据

import torch
import torchvision
import torchvision.transforms as transforms

import matplotlib.pyplot as plt
import numpy as np

import torch.nn as nn
import torch.nn.functional as F


transform = transforms.Compose(
    [
        transforms.ToTensor(),
        transforms.Normalize((0.5, 0.5, 0.5),
                             (0.5, 0.5, 0.5))
    ]
)

trainset = torchvision.datasets.CIFAR10(
    root = './data',
    train = True,
    download = False,
    transform = transform
)

trainloader = torch.utils.data.DataLoader(
    trainset,
    batch_size = 4,
    shuffle = True,
    num_workers = 2
)

testset = torchvision.datasets.CIFAR10(
    root = './data',
    train = False,
    download = False,
    transform = transform
)

testloader = torch.utils.data.DataLoader(
    testset,
    batch_size = 4,
    shuffle = False,
    num_workers = 2
)

classes = ('plane', 'car', 'brid', 'cat',
           'deer', 'dog',