load.py

## parameter denoting the batch size
BATCH_SIZE = 32

## transformations
transform = transforms.Compose(
    [transforms.ToTensor()])

## download and load training dataset
trainset = torchvision.datasets.MNIST(root='./data', train=True,
                                        download=True, transform=transform)
trainloader = torch.utils.data.DataLoader(trainset, batch_size=BATCH_SIZE,
                                          shuffle=True, num_workers=2)

## download and load testing dataset
testset = torchvision.datasets.MNIST(root='./data', train=False,
                                       download=True, transform=transform)
testloader = torch.utils.data.DataLoader(testset, batch_size=BATCH_SIZE,
                                         shuffle=False, num_workers=2)