数据集处理—CIFAR10_clam的博客_cifar10 transform

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

trainset = torchvision.datasets.CIFAR10(root = 'CIFAR10', train = True,
                                        download = True, transform = transform)
trainloader = torch.utils.data.DataLoader(trainset, batch_size = 4,
                                          shuffle = True, num_workers = 2)
#batch_size是每个分组的图片数量


testset = torchvision.datasets.CIFAR10(root = 'CIFAR10', train = False,
                                       download = True, transform = transform)
testloader = torch.utils.data.DataLoader(testset, batch_size = 4,
                                         shuffle = False, num_workers = 2)
classes = ('plane', 'car', 'bird', 'cat',
           'deer', 'dog', 'frog', 'horse', 'ship', 'truck')transform = transforms.Compose(
    [transforms