code: def _parse_record(example_proto):
      features = tf.io.parse_single_example(
          example_proto,
          features={
              "image": tf.io.FixedLenFeature([], tf.string),
              "label": tf.io.FixedLenFeature([], tf.string),
              "comment": tf.io.FixedLenFeature(
                  [], tf.string, default_value=""
              ),
          },
      )
      return features["image"], features["label"], features["comment"]
  
file_path: attention-ocr/aocr/util/data_gen.py
imports: from __future__ import absolute_import
  import sys
  import numpy
  import tensorflow
  from PIL import Image
  from six import BytesIO
  from .bucketdata import BucketData
label_desc: Use image node_id 6 for calling the DataGen obj's underlying member method code with example usage: obj._parse_record(example_proto) and returns: features,  features,  features