text: import os
  os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
  import pickle
  import matplotlib.pyplot as plt
  from util.dataset import load_pkl, load_mnist, load_fmnist, load_svhn
  from certify_add_eps import change_data
  
  data_loader = load_mnist(batch_size = 10, dset = 'test', subset = None)
  data_batch, label_batch = next(data_loader)
  file_data = pickle.load(open('iter1', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  # print(data_batch)
  
  file_data = pickle.load(open('niter2', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  
  file_data = pickle.load(open('niter3', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  
  file_data = pickle.load(open('niter4', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  
  file_data = pickle.load(open('niter5', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  
  file_data = pickle.load(open('iter6', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  
  file_data = pickle.load(open('iter7', 'rb'))
  results_old = file_data['results']
  # print(results_old)
  change = results_old[0]['eps']
  # print(change)
  data_batch = change_data(data_batch, change)
  
  print(data_batch[0])
  fig = plt.figure()
  img = data_batch[0].reshape(28, 28)
  plt.imshow(img, cmap='Greys')
  
  plt.show()
  
  # print(data_batch[0])
  # max = -1.
  # m_idx = 0
  
  # for i in range(784):
  #     if max < data_batch[0][i]:
  #         max = data_batch[0][i]
  #         m_idx = i
  # print(max)
  # print(m_idx)
  
  # file_data = pickle.load(open('iter1', 'rb'))
  # results_old = file_data['results']
  # # # print(results_old)
  # change = results_old[0]['eps']
  # # # print(change)
  # # data_batch[0] = data_batch[0] + change[0]
  # # # print(data_batch)
  
  # print(change[0][355])
  
  # file_data = pickle.load(open('iter2', 'rb'))
  # results_old = file_data['results']
  # # # print(results_old)
  # change = results_old[0]['eps']
  # # # print(change)
  # # data_batch[0] = data_batch[0] + change[0]
  # # # print(data_batch)
  
  # print(change[0][355])
  
  # file_data = pickle.load(open('iter3', 'rb'))
  # results_old = file_data['results']
  # # # print(results_old)
  # change = results_old[0]['eps']
  # # # print(change)
  # # data_batch[0] = data_batch[0] + change[0]
  # # # print(data_batch)
  
  # print(change[0][355])
  
  # file_data = pickle.load(open('iter4', 'rb'))
  # results_old = file_data['results']
  # # # print(results_old)
  # change = results_old[0]['eps']
  # # # print(change)
  # # data_batch[0] = data_batch[0] + change[0]
  # # # print(data_batch)
  
  # print(change[0][355])