code: def __init__(self, batch_size, num_workers=0, shuffle=True):
      super().__init__()
  
      transform = transforms.Compose(
          [
              transforms.ToTensor(),
              transforms.Lambda(lambda x: x * 2.0 - 1.0),
          ]
      )
  
      self.batch_size = batch_size
      self.num_workers = num_workers
      self.shuffle = shuffle
      self.train_dataset = CIFAR10DataDictWrapper(
          torchvision.datasets.CIFAR10(
              root=".data/",
              train=True,
              download=True,
              transform=transform,
          )
      )
      self.test_dataset = CIFAR10DataDictWrapper(
          torchvision.datasets.CIFAR10(
              root=".data/",
              train=False,
              download=True,
              transform=transform,
          )
      )
  
file_path: generative-models/sgm/data/cifar10.py
imports: import pytorch_lightning
  import torchvision
  from torch.utils.data import DataLoader, Dataset
  from torchvision import transforms
label_desc: Use image node_id 1 to create a new CIFAR10Loader object from inherited base classes: pl with example: obj = CIFAR10Loader(batch_size, num_workers, shuffle)