text: import os
  import sys
  
  
  def main():
      current_dir = os.path.dirname(__file__)
      sys.path.append(os.path.join(current_dir, '..'))
      current_dir = current_dir if current_dir is not '' else '.'
  
      from keras_sentiment_analysis.library.cnn_lstm import WordVecCnnLstm
      from keras_sentiment_analysis.library.cnn import WordVecCnn
      from keras_sentiment_analysis.library.cnn import WordVecMultiChannelCnn
      from keras_sentiment_analysis.library.lstm import WordVecLstmSoftmax
      from keras_sentiment_analysis.library.lstm import WordVecLstmSigmoid
      from keras_sentiment_analysis.library.lstm import WordVecBidirectionalLstmSoftmax
  
      classifier = WordVecCnnLstm()
      classifier.load_model(current_dir + '/models')
      classifier.export_tensorflow_model(output_fld=current_dir + '/models/tf')
  
      classifier = WordVecCnn()
      classifier.load_model(current_dir + '/models')
      classifier.export_tensorflow_model(output_fld=current_dir + '/models/tf')
  
      classifier = WordVecMultiChannelCnn()
      classifier.load_model(current_dir + '/models')
      classifier.export_tensorflow_model(output_fld=current_dir + '/models/tf')
  
      classifier = WordVecBidirectionalLstmSoftmax()
      classifier.load_model(current_dir + '/models')
      classifier.export_tensorflow_model(output_fld=current_dir + '/models/tf')
  
      classifier = WordVecLstmSoftmax()
      classifier.load_model(current_dir + '/models')
      classifier.export_tensorflow_model(output_fld=current_dir + '/models/tf')
  
      classifier = WordVecLstmSigmoid()
      classifier.load_model(current_dir + '/models')
      classifier.export_tensorflow_model(output_fld=current_dir + '/models/tf')
  
  
  if __name__ == '__main__':
      main()
  
  