input: Write a python function to train a decision tree classifier using scikit-learn and make a prediction.
  assert train_and_predict([[0, 0], [1, 1]], [0, 1], [[2., 2.]]) == [1]
  assert train_and_predict([[2, 3], [10, 15], [4, 6]], [1, 2, 1], [[5., 7.]]) == [1]
  assert train_and_predict([[1, 2], [3, 4], [5, 6]], [0, 1, 0], [[1., 2.]]) == [0]
output: def train_and_predict(X_train, y_train, X_test):
      from sklearn.tree import DecisionTreeClassifier
  
      clf = DecisionTreeClassifier()
      clf.fit(X_train, y_train)
      return clf.predict(X_test).tolist()