input: 
  from typing import List
  import numpy as np
  from sklearn.svm import SVC
  
  def identify_fruit(training_data: np.ndarray, labels: np.ndarray, test_data: np.ndarray) -> List[int]:
      """
      Develop a machine learning algorithm to identify apples from bananas using a Support Vector Machine (SVM).
      
      >>> training_data = np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]])
      >>> labels = np.array([0, 0, 0, 1, 0, 1])
      >>> test_data = np.array([[2,2,2], [4,4,4]])
      >>> identify_fruit(training_data, labels, test_data)
      [0, 1]
      """
      clf = SVC(kernel='linear')
      clf.fit(training_data, labels)
      return clf.predict(test_data).tolist()
  
output:     clf = SVC(kernel='linear')
      clf.fit(training_data, labels)
      return clf.predict(test_data).tolist()