Question

我正在学习PyTorch，并按照教程进行学习。我发现当我尝试使用torchvision时，我的脚本运行了两次。我想知道它是否配置错误，还是我不小心引入了某种并行性。

这是我的代码：

# show images
import torch
import torchvision
import torchvision.transforms as transforms
import matplotlib.pyplot as plt
import numpy as np

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=True, 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=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')

def imshow(img):
    img = img / 2 + 0.5     # unnormalize
    npimg = img.numpy()
    plt.imshow(np.transpose(npimg, (1, 2, 0)))
    plt.show()


# get some random training images
print('Type of trainloader')
print(type(trainloader))

dataiter = iter(trainloader)
images, labels = dataiter.next()

# show images
imshow(torchvision.utils.make_grid(images))
# print labels
print(' '.join('%5s' % classes[labels[j]] for j in range(4)))

我的输出是：

C:\Users\Avi\Anaconda3\python.exe C:/Users/Avi/PycharmProjects/ExampleNN/test.py
Files already downloaded and verified
Files already downloaded and verified
Type of trainloader
<class 'torch.utils.data.dataloader.DataLoader'>
Files already downloaded and verified
Files already downloaded and verified
Type of trainloader
<class 'torch.utils.data.dataloader.DataLoader'>

然后dataiter = iter(trainloader)第二次崩溃，大概是因为迭代已经完成。

有人可以告诉我我在做什么错吗？

更新：

我发现，如果我在DataLoader构造函数中设置num_workers = 0，则它只会运行一次，并且不会崩溃。如果将其设置为1，它会运行两次并像将其设置为2一样崩溃。我仍然不明白为什么会这样，但是至少我可以解决我的问题。

Python Script自身运行两次

0 个答案: