input: def identify_fruit(X: np.ndarray, y: np.ndarray, x_test: np.ndarray) -> np.ndarray:
      """ Develop a machine learning algorithm to identify apples (label 0) from bananas (label 1) using a linear SVM classifier.
      The function takes training data X with labels y and test data x_test, fits the data with a classifier, and returns the predictions.
      >>> X = np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]])
      >>> y = np.array([0, 0, 0, 1, 0, 1])
      >>> x_test = np.array([[2,2,2], [4,4,4]])
      >>> identify_fruit(X, y, x_test)
      array([0, 1])
      """
      clf = SVC(kernel='linear')
      clf.fit(X, y)
      return clf.predict(x_test)
output:     from sklearn.svm import SVC