code: def ld_cifar10():
      """Load training and test data."""
      train_transforms = torchvision.transforms.Compose(
          [torchvision.transforms.ToTensor()]
      )
      test_transforms = torchvision.transforms.Compose(
          [torchvision.transforms.ToTensor()]
      )
      train_dataset = torchvision.datasets.CIFAR10(
          root="/tmp/data",
          train=True,
          transform=train_transforms,
          download=True,
      )
      test_dataset = torchvision.datasets.CIFAR10(
          root="/tmp/data",
          train=False,
          transform=test_transforms,
          download=True,
      )
      train_loader = torch.utils.data.DataLoader(
          train_dataset, batch_size=128, shuffle=True, num_workers=2
      )
      test_loader = torch.utils.data.DataLoader(
          test_dataset, batch_size=128, shuffle=False, num_workers=2
      )
      return EasyDict(train=train_loader, test=test_loader)
  
file_path: cleverhans/tutorials/torch/cifar10_tutorial.py
imports: from absl import app, flags
  from easydict import EasyDict
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision
  from cleverhans.torch.attacks.fast_gradient_method import fast_gradient_method
  from cleverhans.torch.attacks.projected_gradient_descent import projected_gradient_descent
label_desc: Use image node_id 1 for calling a global function with example usage: ld_cifar10() and returns: EasyDict