code: def predict(self, x, return_names=True):
      label_codes = self.model.predict(
          x.reshape(-1, IrisModel.NUM_FEATURES)
      )
  
      if return_names:
          predictions = [
              IrisModel.LABELS(code).name for code in label_codes
          ]
      else:
          predictions = label_codes.tolist()
  
      return predictions
  
file_path: sagemaker-python-sdk/tests/data/marketplace/iris/scoring_logic.py
imports: from enum import IntEnum
  import json
  import logging
  import re
  from flask import Flask
  from flask import request
  from joblib import dump, load
  import numpy
  import os
label_desc: Use image node_id 6 for calling the IrisModel obj's underlying member method code with example usage: obj.predict(x, return_names) and returns: predictions