code: def read_imagenet(path: str, is_training: bool):
      """
      Convert ImageNet TFRecords files to tf.data.Dataset
  
      Args:
      data_dir: ImageNet TFRecords data path. It supports local path or hdfs path. If you use
                hdfs path, please make sure set environment variables LD_LIBRARY_PATH within PATH.
              - Training images: train/train-00000-of-01024
              - Validation Images: validation/validation-00000-of-00128
      is_training: True or False. train dataset or val dataset
  
      """
      filenames = get_filenames(is_training, path)
      dataset = tf.data.Dataset.from_tensor_slices(filenames)
  
      # Convert to individual records
      dataset = dataset.interleave(
          tf.data.TFRecordDataset,
          num_parallel_calls=tf.data.experimental.AUTOTUNE,
      )
      return dataset
  
file_path: analytics-zoo/pyzoo/zoo/orca/data/image/tfrecord_dataset.py
imports: import os
  import tensorflow
  from zoo.orca.data.image.imagenet_dataset import *
  from zoo.orca.data.image.parquet_dataset import _check_arguments
label_desc: Use image node_id 2 for calling a global function with example usage: read_imagenet(path, is_training) and returns: dataset