input: Write a python function to train a Gaussian Naive Bayes model and make predictions.
  assert train_and_predict([[1, 2], [3, 4]], [0, 1], [[1, 2]]) == 0
  assert train_and_predict([[5, 6], [7, 8]], [1, 0], [[5, 6]]) == 1
  assert train_and_predict([[9, 10], [11, 12]], [0, 1], [[9, 10]]) == 0
output: def train_and_predict(train_data, train_labels, test_data):
      from sklearn.naive_bayes import GaussianNB
      model = GaussianNB()
      model.fit(train_data, train_labels)
      return model.predict(test_data)[0]