text: import matplotlib.pyplot as plt
  import numpy as np
  
  def plot_accuracies(history):
      accuracies = [x['val_acc'] for x in history]
      plt.plot(accuracies, '-x')
      plt.xlabel('epoch')
      plt.ylabel('accuracy')
      plt.title('Accuracy vs. No. of epochs')
      plt.savefig('accuracy.png')
      plt.show()
  
  
  
  def plot_losses(history):
      train_losses = [x.get('train_loss') for x in history]
      val_losses = [x['val_loss'] for x in history]
      plt.plot(train_losses, '-bx')
      plt.plot(val_losses, '-rx')
      plt.xlabel('epoch')
      plt.ylabel('loss')
      plt.legend(['Training', 'Validation'])
      plt.title('Loss vs. No. of epochs')
      plt.savefig('loss.png')
      plt.show()
  
  def plot_lrs(history):
      lrs = np.concatenate([x.get('lrs', []) for x in history])
      plt.plot(lrs)
      plt.xlabel('Batch no.')
      plt.ylabel('Learning rate')
      plt.title('Learning Rate vs. Batch no.');
      plt.savefig('learning_rate.png')
      plt.show()