input: from typing import List
  
  def identify_apples_bananas_from_color(X: List[List[float]], y: List[int]) -> List[int]:
      """
      Given a list of 3D coordinates representing the color attributes of various fruits 
      and a corresponding list of integers indicating whether the fruit is an apple (0) or 
      banana (1), train a Support Vector Machine (SVM) classifier and make predictions on 
      new data.
      
      >>> identify_apples_bananas_from_color([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]], [0, 0, 0, 1, 0, 1]) 
      [0, 1]
      """
      import numpy as np
      from sklearn.svm import SVC
  
      X_np = np.array(X)
      y_np = np.array(y)
      x_test = np.array([[2,2,2], [4,4,4]])
      
      clf = SVC(kernel='linear')
      clf.fit(X_np, y_np)
      prediction = clf.predict(x_test)
      
      return prediction.tolist()
output:     import numpy as np
      from sklearn.svm import SVC
  
      X_np = np.array(X)
      y_np = np.array(y)
      x_test = np.array([[2,2,2], [4,4,4]])
      
      clf = SVC(kernel='linear')
      clf.fit(X_np, y_np)
      prediction = clf.predict(x_test)
      
      return prediction.tolist()