code: def ld_mnist():
      """Load training and test data."""
      train_transforms = torchvision.transforms.Compose(
          [torchvision.transforms.ToTensor()]
      )
      test_transforms = torchvision.transforms.Compose(
          [torchvision.transforms.ToTensor()]
      )
  
      # Load MNIST dataset
      train_dataset = MNISTDataset(
          root="/tmp/data", transform=train_transforms
      )
      test_dataset = MNISTDataset(
          root="/tmp/data", train=False, transform=test_transforms
      )
  
      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/mnist_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 datasets import MNISTDataset
  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_mnist() and returns: EasyDict