code: def inference(cls, architecture_name, architecture_path, image_path):
      if cls.sanity_check(architecture_name):
          import numpy as np
  
          func = TestKit.preprocess_func["cntk"][architecture_name]
          img = func(image_path)
          img = np.transpose(img, (2, 0, 1))
          model = C.Function.load(architecture_path)
          predict = model.eval({model.arguments[0]: [img]})
          predict = np.squeeze(predict)
  
          top_indices = predict.argsort()[-5:][::-1]
          return predict
  
      else:
          return None
  
file_path: MMdnn/mmdnn/conversion/examples/cntk/extractor.py
imports: from __future__ import absolute_import
  import cntk
  from mmdnn.conversion.examples.imagenet_test import TestKit
  from mmdnn.conversion.examples.extractor import base_extractor
  from mmdnn.conversion.common.utils import download_file
label_desc: Use image node_id 2 for calling the cntk_extractor obj's underlying member method code with example usage: obj.inference(cls, architecture_name, architecture_path, image_path) and returns: predict, None