code: def get_nn_classifier(X, y):
      
      assert type(X) is numpy.ndarray
      assert type(y) is numpy.ndarray
      assert len(X) == len(y)
      assert X.dtype == 'float32'
      assert y.dtype == 'int32'
  
      nn_pickled_filename = 'is_one_symbol_classifier.pickle'
      if os.path.isfile(nn_pickled_filename):
          with open(nn_pickled_filename, 'rb') as handle:
              get_output = pickle.load(handle)
      else:
          get_output = train_nn_segmentation_classifier(X, y)
          with open(nn_pickled_filename, 'wb') as handle:
              pickle.dump(get_output, handle, protocol=pickle.HIGHEST_PROTOCOL)
      return get_output
docs: Train a neural network classifier.
  
      Parameters
      ----------
      X : numpy array
          A list of feature vectors
      y : numpy array
          A list of labels
  
      Returns
      -------
      Theano expression :
          The trained neural network