text: from random import shuffle
  
  import numpy as np
  
  from keras_cn_parser_and_analyzer.library.classifiers.cnn import WordVecMultiChannelCnn
  from keras_cn_parser_and_analyzer.library.utility.simple_data_loader import load_text_label_pairs
  
  
  def main():
      random_state = 42
      np.random.seed(random_state)
  
      model_dir_path = './models'
      data_file_path = '../data/training_data'
      text_label_pairs = load_text_label_pairs(data_file_path, label_type='line_label')
  
      classifier = WordVecMultiChannelCnn()
      classifier.load_model(model_dir_path=model_dir_path)
  
      shuffle(text_label_pairs)
  
      for i in range(20):
          text, label = text_label_pairs[i]
          print('Output: ', classifier.predict(sentence=text))
          predicted_label = classifier.predict_class(text)
          print('Sentence: ', text)
          print('Predicted: ', predicted_label, 'Actual: ', label)
  
  
  if __name__ == '__main__':
      main()
  