input: def identify_fruit(X_train: np.array, y_train: np.array, X_test: np.array) -> np.array:
      """
      Develop a machine learning algorithm using SVM to identify apples (labeled as 0) from bananas (labeled as 1).
      >>> X_train = np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]])
      >>> y_train = np.array([0, 0, 0, 1, 0, 1])
      >>> X_test = np.array([[2,2,2], [4,4,4]])
      >>> identify_fruit(X_train, y_train, X_test)
      array([0, 1])
      """
      clf = SVC(kernel='linear')
      clf.fit(X_train, y_train)
      prediction = clf.predict(X_test)
      return prediction
output:     from sklearn.svm import SVC