input: 
  from sklearn.naive_bayes import GaussianNB
  
  def naive_bayes_classifier(X_train, y_train, X_test):
      """ Constructs a naive bayes classifier using scikit-learn's Gaussian Naive Bayes
      classifier. Trains the model on the given training data and predicts the output
      for the test data.
      >>> X_train = [[1, 2], [3, 4], [5, 6]]
      >>> y_train = [0, 1, 0]
      >>> X_test = [[7, 8]]
      >>> naive_bayes_classifier(X_train, y_train, X_test)
      array([1])
      """
      model = GaussianNB()
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      return y_pred
  
output:     model = GaussianNB()
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      return y_pred