text: import numpy as np
  import sys
  import os
  
  
  def main():
      random_state = 42
      np.random.seed(random_state)
  
      current_dir = os.path.dirname(__file__)
      sys.path.append(os.path.join(current_dir, '..'))
      current_dir = current_dir if current_dir is not '' else '.'
  
      output_dir_path = current_dir + '/models'
      data_file_path = current_dir + '/data/umich-sentiment-train.txt'
  
      from keras_sentiment_analysis.library.ffn import WordVecGloveFFN
      from keras_sentiment_analysis.library.utility.simple_data_loader import load_text_label_pairs
      from keras_sentiment_analysis.library.utility.text_fit import fit_text
  
      text_data_model = fit_text(data_file_path)
      text_label_pairs = load_text_label_pairs(data_file_path)
  
      classifier = WordVecGloveFFN()
      classifier.load_glove_model(data_dir_path='./very_large_data')
      batch_size = 64
      epochs = 20
      history = classifier.fit(text_data_model=text_data_model,
                               model_dir_path=output_dir_path,
                               text_label_pairs=text_label_pairs,
                               batch_size=batch_size, epochs=epochs,
                               test_size=0.3,
                               random_state=random_state)
  
  
  if __name__ == '__main__':
      main()
  