我正在尝试迭代我的数据集,并获得第一个元素
transform = transforms.Compose([transforms.ToTensor(),transforms.Normalize((0.5),(0.5)),])
trainloader = datasets.MNIST('~/.pytorch/MNIST_data' , download=True,train=True , transform=transform)
ds = iter(trainloader)
img, labels = ds.next()
但是它返回这个错误
AttributeError: 'iterator' object has no attribute 'next'
我也试过这个
img , labels = next(ds)
返回此错误
StopIteration:
我错过什么了吗?
可能是这个问题:https://github.com/microsoft/DeepSpeedExamples/issues/222
然后更改为:
images, labels = dataiter.next()
至:
images, labels = next(dataiter)
如果您按照https://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html
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)
dataiter = iter(trainloader)
images, labels = dataiter.next()
数据集上缺少DataLoader((函数