code: def parse_example_proto_and_decode(example_serialized):
      """Parses an example and decodes the image to prepare for caching."""
      image_buffer, label = _parse_example_proto(example_serialized)
      image_buffer = tf.reshape(image_buffer, shape=[])
      image_buffer = tf.io.decode_jpeg(
          image_buffer, channels=NUM_CHANNELS
      )
      return image_buffer, label
  
file_path: ray/release/air_tests/air_benchmarks/mlperf-train/tf_utils.py
imports: import tensorflow
  import functools
  import logging
label_desc: Use image node_id 3 for calling a global function with example usage: parse_example_proto_and_decode(example_serialized) and returns: image_buffer,  label