code: def create_single_example(image_url: str) -> tf.train.Example:
      image_buffer, height, width = parse_single_image(image_url)
  
      colorspace = "RGB"
      channels = 3
      image_format = "JPEG"
      label = 0
      synset = "dummy-synset"
      filename = "dummy-filename"
  
      example = tf.train.Example(
          features=tf.train.Features(
              feature={
                  "image/height": _int64_feature(height),
                  "image/width": _int64_feature(width),
                  "image/colorspace": _bytes_feature(colorspace),
                  "image/channels": _int64_feature(channels),
                  "image/class/label": _int64_feature(label),
                  "image/class/synset": _bytes_feature(synset),
                  "image/format": _bytes_feature(image_format),
                  "image/filename": _bytes_feature(
                      os.path.basename(filename)
                  ),
                  "image/encoded": _bytes_feature(image_buffer),
              }
          )
      )
  
      return example
  
imports: from typing import Union, Iterable, Tuple, Optional
  import os
  import requests
  import shutil
  import sys
  import tensorflow.compat.v1
  import time
  from ray.util.scheduling_strategies import NodeAffinitySchedulingStrategy
  import ray
label_desc: Use image node_id 8 for calling a global function with example usage: create_single_example(image_url) and returns: example