code: def load_challenge():
      """
      Load the challenge datast for attacking
      """
      global xs, ys, encoded, original, ooriginal
      print("SETUP: Loading matrixes")
      # The encoded images
      encoded = np.load("challenge-7.npy")
      # And the original images
      ooriginal = original = np.load("orig-7.npy")
  
      print("Sizes", encoded.shape, ooriginal.shape)
  
      # Again do that ugly resize thing to make the features be on the last dimension
      # Look up above to see what's going on.
      patch_size = 16
      ss = original.shape[2] // patch_size
      original = ooriginal.reshape(
          (original.shape[0], 1, ss, patch_size, ss, patch_size)
      )
      original = original.transpose((0, 2, 4, 1, 3, 5))
      original = original.reshape(
          (original.shape[0], ss**2, patch_size**2)
      )
  
imports: import collections
  import hashlib
  import time
  import multiprocessing
  import torch
  import numpy
  import torch.nn
  import scipy.stats
  import matplotlib.pyplot
  from PIL import Image
  import jax
  import jax.numpy
  import objax
  import scipy.optimize
  import numpy
  import multiprocessing
label_desc: Use image node_id 7 for calling a global function with example usage: load_challenge() without return types