80f2930151b0eeaa393ff0441917f783da3f1561,examples/pytorch_simple.py,,get_mnist,#,76

Before Change

    kwargs = {"num_workers": 1, "pin_memory": True} if DEVICE.type == "cuda" else {}
    train_loader = torch.utils.data.DataLoader(
        datasets.MNIST(DIR, train=True, download=True,
                       transform=transforms.Compose([
                           transforms.ToTensor(),
                           transforms.Normalize((0.1307,), (0.3081,))
                       ])),
        batch_size=BATCHSIZE, shuffle=True, **kwargs)
    test_loader = torch.utils.data.DataLoader(
        datasets.MNIST(DIR, train=False,
                       transform=transforms.Compose([
                           transforms.ToTensor(),
                           transforms.Normalize((0.1307,), (0.3081,))
                       ])),
        batch_size=BATCHSIZE, shuffle=True, **kwargs)

    return (train_loader, test_loader)

After Change

    train_loader = torch.utils.data.DataLoader(datasets.MNIST(DIR,
                                                              train=True,
                                                              download=True,
                                                              transform=transforms.ToTensor()),
                                               batch_size=BATCHSIZE,
                                               shuffle=True)
    test_loader = torch.utils.data.DataLoader(datasets.MNIST(DIR,

Instances