text: import torch
  from torch.utils.data import DataLoader
  import torchvision.datasets as datasets
  import torchvision.transforms as T
  from torch.utils.data import TensorDataset
  
  data_route  = './data/' # EDIT THIS!
  cifar_nm    = T.Normalize((0.4914,0.4822,0.4465),(0.247,0.243,0.261))
  
  def get_dataset(dataset):
      if dataset == 'cifar10':
  	    tfm_train   = T.Compose([T.RandomCrop(32, padding=4),T.RandomHorizontalFlip(),T.ToTensor(),cifar_nm])
  	    tfm_test    = T.Compose([T.ToTensor(),cifar_nm])
  	    train_set   = datasets.CIFAR10(data_route,train=True,download=True,transform=tfm_train)
  	    test_set    = datasets.CIFAR10(data_route,train=False,download=False,transform=tfm_test)
      else:
          raise ValueError('Unknown dataset')
      return train_set, test_set
  
  def get_loader(dataset,batch_size=100):
      print("Loading "+dataset+" with batch_size "+str(batch_size))
      train_set,test_set  = get_dataset(dataset)
      train_loader    = DataLoader(train_set,batch_size=batch_size,shuffle=True,drop_last=True)
      test_loader     = DataLoader(test_set,batch_size=batch_size,shuffle=False,drop_last=False)
      return train_loader,test_loader