code: def get_dataset(cls, cutout_length=0):
      MEAN = [0.49139968, 0.48215827, 0.44653124]
      STD = [0.24703233, 0.24348505, 0.26158768]
      transf = [
          transforms.RandomCrop(32, padding=4),
          transforms.RandomHorizontalFlip(),
      ]
      normalize = [
          transforms.ToTensor(),
          transforms.Normalize(MEAN, STD),
      ]
      cutout = []
      if cutout_length > 0:
          cutout.append(Cutout(cutout_length))
  
      train_transform = transforms.Compose(transf + normalize + cutout)
      valid_transform = transforms.Compose(normalize)
  
      if cls == "cifar10":
          dataset_train = CIFAR10(
              root="./data",
              train=True,
              download=True,
              transform=train_transform,
          )
          dataset_valid = CIFAR10(
              root="./data",
              train=False,
              download=True,
              transform=valid_transform,
          )
      else:
          raise NotImplementedError
      return dataset_train, dataset_valid
  
file_path: nni/examples/nas/legacy/oneshot/darts/datasets.py
imports: import numpy
  import torch
  from torchvision import transforms
  from torchvision.datasets import CIFAR10
label_desc: Use image node_id 1 for calling a global function with example usage: get_dataset(cls, cutout_length) and returns: dataset_train,  dataset_valid