Test the PyTorch example and try to download the data using the following code. It is too slow.

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

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

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So I manually downloaded the data. After a bit of research, it became clear that Pytorch was required to load data

  1. Specify a directory$root
  2. in$rootUnzip the data package
  3. The folder decompressed cannot be renamed.

Using the CIFAR10 data set as an example, the decompressed directory must be $root/ CIFAR-10-BATCHES -py, and $root (in this example,.data) is sent as an additional parameter