input: Write a function to create a machine learning algorithm in Python to identify apples from bananas using a Support Vector Classifier. The function should initialize the classifier, fit the training data, and predict the class for the test data. The function should return the predictions for the test data.
  
  def identify_fruit(X_train, y_train, X_test):
      from sklearn.svm import SVC
      clf = SVC(kernel='linear')
      clf.fit(X_train, y_train)
      return clf.predict(X_test)
  
  assert np.array_equal(identify_fruit(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_fruit(X_train, y_train, X_test):
      from sklearn.svm import SVC
      clf = SVC(kernel='linear')
      clf.fit(X_train, y_train)
      return clf.predict(X_test)