text: import numpy as np
  import pickle
  import matplotlib.pyplot as plt
  
  epc = []
  maxepoch = 100
  box_train_loss = []
  box_test_loss = []
  box_train_acc = []
  box_test_acc = []
  
  with open ('log.pkl', 'rb') as f:
  	d = pickle.Unpickler(f).load()
  
  for epoch in range(maxepoch):
  	epc.append(epoch)
  	box_train_loss.append(d['train_loss'][epoch])
  	box_test_loss.append(d['test_loss'][epoch])
  	box_train_acc.append(d['train_acc'][epoch])
  	box_test_acc.append(d['test_acc'][epoch])
  
  fig, (loss, acc) = plt.subplots(ncols=2, figsize=(10, 4))
  
  loss.plot(epc, box_train_loss, label='train')
  loss.plot(epc, box_test_loss, label='test')
  loss.set_title('Model loss')
  loss.set_xlabel('Epoch')
  loss.set_ylabel('Loss')
  loss.legend()
  
  acc.plot(epc, box_train_acc, label='train')
  acc.plot(epc, box_test_acc, label='test')
  acc.set_title('Model accuracy')
  acc.set_xlabel('Epoch')
  acc.set_ylabel('Accuracy')
  acc.legend(loc="lower right")
  
  plt.show()
  