input: Write a python function to train an AdaBoost classifier and make a prediction.
  assert train_and_predict_ada_boost([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]], [1, 1, 1, 2, 2, 2], [[-0.8, -1]])==[1]
  assert train_and_predict_ada_boost([[0, 0], [1, 1], [1, 0], [0, 1]], [0, 1, 1, 0], [[0.5, 0.5]])==[1]
  assert train_and_predict_ada_boost([[-1, -1], [-1, 1], [1, -1], [1, 1]], [1, 2, 2, 1], [[0, 0]])==[1]
output: def train_and_predict_ada_boost(X_train, y_train, X_test):
      from sklearn.ensemble import AdaBoostClassifier
      
      # Train the AdaBoost classifier
      model = AdaBoostClassifier()
      model.fit(X_train, y_train)
      
      # Make predictions on the test set
      predictions = model.predict(X_test)
      return list(predictions)