AttributeError: 'str' object has no attribute 'jion' 报错怎么解决?
```python
# 下载预处理CIFAR10数据集
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
import torch.optim as optim
# 定义数据预处理方法
# torchvision.transforms是pytorch中的图像预处理包。一般用Compose把多个步骤整合到一起
transforms = transforms.Compose(
[transforms.ToTensor(),
transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
# 下载数据集并载入数据
trainset = torchvision.datasets.CIFAR10(root='./data', train=True,
download=True, transform=transforms)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=4,
shuffle=True, num_workers=0)
testset = torchvision.datasets.CIFAR10(root='./data', train=False,
download=True, transform=transforms)
testloader = torch.utils.data.DataLoader(testset, batch_size=4,
shuffle=True, num_workers=0)
# 数据类别标签
classes = ('plane', 'car', 'bird', 'cat',
'deer', 'dog', 'frog',
'horse', 'ship', 'truck')
# 显示图像
def imshow(img):
img = img / 2 + 0.5 # unnormalize
npimg = img.numpy()
plt.imshow(np.transpose(npimg, (1, 2, 0)))
plt.show()
if __name__ == '__main__':
# 随机读取一些数据
dataiter = iter(trainloader)
# images, labels = dataiter.next()
images, labels = next(dataiter)
# 显示图像
imshow(torchvision.utils.make_grid(images))
# print labels
print(''.jion('%5s' % classes[labels[j]] for j in range(4)))