input: Write a python function to train an SVM classifier with an RBF kernel and make predictions using provided training data.
  assert svm_classifier([[1, 2], [2, 3], [3, 4]], [0, 1, 0]) == [0, 1, 0]
  assert svm_classifier([[1, 1], [2, 2], [3, 3]], [1, 0, 1]) == [1, 0, 1]
  assert svm_classifier([[1, 2], [2, 3], [3, 4], [4, 5]], [0, 1, 0, 1]) == [0, 1, 0, 1]
output: def svm_classifier(X_train, y_train):
      from sklearn.svm import SVC
      model = SVC(kernel='rbf')
      model.fit(X_train, y_train)
      return model.predict(X_train).tolist()