input: Write a python function to train an SVM model using scikit-learn and make predictions.
  assert train_and_predict_svm([[0, 0], [1, 1]], [0, 1], [[2., 2.]]) == [1]
  assert train_and_predict_svm([[2, 2], [3, 3]], [1, 0], [[1., 1.]]) == [1]
  assert train_and_predict_svm([[1, 2], [2, 3], [3, 4]], [0, 1, 1], [[2., 2.]]) == [1]
output: def train_and_predict_svm(X_train, y_train, X_test):
      from sklearn import svm
      clf = svm.SVC()
      clf.fit(X_train, y_train)
      return clf.predict(X_test).tolist()