input: Write a function to implement a machine learning algorithm in Python to identify apples from bananas using a Support Vector Machine. The function should initialize the classifier, fit the data, and then test the classifier by predicting the classes of the provided test data. Return the prediction results.
  assert identify_apple_banana(np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]]), np.array([0, 0, 0, 1, 0, 1]), np.array([[2,2,2], [4,4,4]]))==np.array([0, 1])
output: def identify_apple_banana(train_data, train_labels, test_data):
      from sklearn import svm
      clf = svm.SVC()
      clf.fit(train_data, train_labels)
      predictions = clf.predict(test_data)
      return predictions