code: def test_resnet50(self):
      from tensorflow.keras.applications.resnet_v2 import (
          decode_predictions,
      )
      from tensorflow.keras.applications.resnet_v2 import (
          preprocess_input,
      )
  
      images = self.load_imagenet_images(preprocess_input)
      model = tf.keras.applications.ResNet50V2(weights="imagenet")
      preds = model.predict(images)
      print_banner(
          "Convert Plain "
          + model.name.capitalize()
          + " to TFE "
          + model.name.capitalize()
      )
      print(
          "Plain model predicted:", decode_predictions(preds, top=10)[0]
      )
      self.tfe_model_predict(model, images, decode_predictions)
  
file_path: tf-encrypted/examples/benchmark/inference/convert.py
imports: import argparse
  import os
  import unittest
  import _pickle
  import numpy
  import tensorflow
  import tf_encrypted
  from tf_encrypted.convert import convert
  from tf_encrypted.performance import Performance
  from tf_encrypted.protocol import ABY3
  from tf_encrypted.protocol import Pond
  from tf_encrypted.protocol import SecureNN
  from tf_encrypted.utils import print_banner
label_desc: Use image node_id 5 for calling the TestConvertInference obj's underlying member method code with example usage: obj.test_resnet50() without return types