input: 
  def identify_fruits(X: np.ndarray, y: np.ndarray, x_test: np.ndarray) -> np.ndarray:
      """Develop a machine learning algorithm in Python to identify apples from bananas using Support Vector Machine (SVM).
      The input features are represented by a numpy array X, and the corresponding labels are represented by a numpy array y.
      The function should train the classifier on the provided data and then predict the labels for the given test data.
  
      >>> identify_fruits(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]]))
      array([0, 1])
      """
      clf = SVC(kernel='linear')
      clf.fit(X, y)
      return clf.predict(x_test)
  
output:     import numpy as np
      from sklearn.svm import SVC