code: def multi_classification_two_features(input_vector):
      # Define the number of divisions for each feature
      divisions = 5
  
      # Calculate the division size for each feature
      division_size = 1 / divisions
  
      # Calculate the class index based on the input vector's position in the feature space
      class_idx = int(
          input_vector[0] // division_size
      ) * divisions + int(input_vector[1] // division_size)
  
      return class_idx + 1
  
label_desc: Use image node_id 2 for calling a global function with example usage: multi_classification_two_features(input_vector) and returns: unknown