text: import unittest
  from src.model.text2vec import Text2Vec
  from src.model.random_forest import RandomForest
  
  
  class TestText2Vec(unittest.TestCase):
      def test_text2vec(self):
          sample = Text2Vec(build_on_corpus=False)
          sample.build_model()
          sample.train_model()
          sample.infer_embedding('train')
          sample.infer_embedding('dev')
          sample.load_model()
          X_train, y_train = sample.load_embedding('train')
          X_dev, y_dev = sample.load_embedding('dev')
          random_forest = RandomForest('text', X_train, y_train, X_dev, y_dev, test=True)
          random_forest.run()
          random_forest.evaluate()
          sample.evaluate_model()
      
      def test_most_similar(self):
          text2vec = Text2Vec()
          text2vec.dm = 1
          text2vec.vector_size = 50
          text2vec.window_size = 10
          text2vec.negative = 5
          text2vec.hs = 0
          text2vec.build_model()
          text2vec.load_model()
          text2vec.evaluate_model()
          # text2vec.process_metadata_tensorboard()
  
  
  if __name__ == "__main__":
      unittest.main()