code: def test_cifar10_dataset():
      # build transform
      transform_pipeline = [transforms.ToTensor()]
      transform_pipeline = transforms.Compose(transform_pipeline)
  
      # build dataset
      dataset = datasets.CIFAR10(
          root=Path(os.environ["DATA"]),
          train=True,
          download=True,
          transform=transform_pipeline,
      )
  
      # build dataloader
      dataloader = DataLoader(
          dataset=dataset, batch_size=4, shuffle=True, num_workers=2
      )
      data_iter = iter(dataloader)
      img, label = data_iter.next()
  
imports: import os
  from pathlib import Path
  from torch.utils.data import DataLoader
  from torchvision import datasets, transforms
label_desc: Use image node_id 1 for calling a global function with example usage: test_cifar10_dataset() without return types