Preprocessing, download and create loader from dataset

dataset.py

# Define a transform to normalize the data
transform = transforms.Compose([transforms.ToTensor(),
                                transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))])
# Download and load the training data
trainset = datasets.FashionMNIST('F_MNIST_data/', download=True, train=True, transform=transform)

# Download and load the test data
testset = datasets.FashionMNIST('F_MNIST_data/', download=True, train=False, transform=transform)

loaders = {
    'train' : torch.utils.data.DataLoader(trainset,batch_size = 64,shuffle=True),
    'test'  : torch.utils.data.DataLoader(testset,batch_size = 64,shuffle=True),
}