code: def load_testset(size):
      # Load images paths and labels
      pairs = lfw.read_pairs(pairs_path)
      paths, labels = lfw.get_paths(testset_path, pairs)
  
      # Random choice
      permutation = np.random.choice(len(labels), size, replace=False)
      paths_batch_1 = []
      paths_batch_2 = []
  
      for index in permutation:
          paths_batch_1.append(paths[index * 2])
          paths_batch_2.append(paths[index * 2 + 1])
  
      labels = np.asarray(labels)[permutation]
      paths_batch_1 = np.asarray(paths_batch_1)
      paths_batch_2 = np.asarray(paths_batch_2)
  
      # Load images
      faces1 = facenet.load_data(
          paths_batch_1, False, False, image_size
      )
      faces2 = facenet.load_data(
          paths_batch_2, False, False, image_size
      )
  
      # Change pixel values to 0 to 1 values
      min_pixel = min(np.min(faces1), np.min(faces2))
      max_pixel = max(np.max(faces1), np.max(faces2))
      faces1 = (faces1 - min_pixel) / (max_pixel - min_pixel)
      faces2 = (faces2 - min_pixel) / (max_pixel - min_pixel)
  
      # Convert labels to one-hot vectors
      onehot_labels = []
      for index in range(len(labels)):
          if labels[index]:
              onehot_labels.append([1, 0])
          else:
              onehot_labels.append([0, 1])
  
      return faces1, faces2, np.array(onehot_labels)
  
file_path: cleverhans/cleverhans_v3.1.0/examples/facenet_adversarial_faces/set_loader.py
imports: import shutil
  import os
  import lfw
  import facenet
  import numpy
  from PIL import Image
label_desc: Use image node_id 3 for calling a global function with example usage: load_testset(size) and returns: faces1,  faces2,  np