code: def predict_input(itos_filename, trained_classifier_filename, num_classes=2):
      
      # Check the itos file exists
      if not os.path.exists(itos_filename):
          print("Could not find " + itos_filename)
          exit(-1)
  
      # Check the classifier file exists
      if not os.path.exists(trained_classifier_filename):
          print("Could not find " + trained_classifier_filename)
          exit(-1)
  
      stoi, model = load_model(itos_filename, trained_classifier_filename, num_classes)
  
      while True:
          text = input("Enter text to analyse (or q to quit): ")
          if text.strip() == 'q':
              break
          else:
              scores = predict_text(stoi, model, text)
              print("Result id {0}, Scores: {1}".format(np.argmax(scores), scores))
docs: Loads a model and produces predictions on arbitrary input.
      :param itos_filename: the path to the id-to-string mapping file
      :param trained_classifier_filename: the filename of the trained classifier;
                                          typically ends with "clas_1.h5"
      :param num_classes: the number of classes that the model predicts