code: def __init__(self, **kwargs):
      super(TFRecordPipeline, self).__init__(**kwargs)
      tfrecord = sorted(glob.glob(kwargs["data_paths"][0]))
      tfrecord_idx = sorted(glob.glob(kwargs["data_paths"][1]))
      cache_enabled = kwargs["decoder_cache_params"]["cache_enabled"]
      self.input = ops.readers.TFRecord(
          path=tfrecord,
          index_path=tfrecord_idx,
          shard_id=kwargs["shard_id"],
          num_shards=kwargs["num_shards"],
          random_shuffle=kwargs["random_shuffle"],
          dont_use_mmap=kwargs["dont_use_mmap"],
          stick_to_shard=cache_enabled,
          features={
              "image/encoded": tfrec.FixedLenFeature(
                  (), tfrec.string, ""
              ),
              "image/class/label": tfrec.FixedLenFeature(
                  [1], tfrec.int64, -1
              ),
          },
      )
  
imports: from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.ops
  import nvidia.dali.types
  import nvidia.dali.tfrecord
  import os
  import glob
  import argparse
  import time
  from test_utils import get_dali_extra_path, AverageMeter
label_desc: Use image node_id 1 to create a new TFRecordPipeline object from inherited base classes: CommonPipeline with example: obj = TFRecordPipeline()