code: def __init__(
      self,
      data_paths,
      batch_size,
      num_threads,
      shard_id,
      num_gpus,
      random_shuffle,
      stick_to_shard,
      shuffle_after_epoch,
      pad_last_batch,
      initial_fill=1024,
  ):
      # use only 1 GPU, as we care only about shard_id
      super().__init__(
          batch_size, num_threads, 0, prefetch_queue_depth=1
      )
      self.input = ops.readers.COCO(
          file_root=data_paths[0],
          annotations_file=data_paths[1],
          shard_id=shard_id,
          num_shards=num_gpus,
          random_shuffle=random_shuffle,
          image_ids=True,
          stick_to_shard=stick_to_shard,
          shuffle_after_epoch=shuffle_after_epoch,
          pad_last_batch=pad_last_batch,
          initial_fill=initial_fill,
      )
  
imports: import nose_utils
  import math
  from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.ops
  import numpy
  import os
  from test_utils import get_dali_extra_path
label_desc: Use image node_id 1 to create a new COCOReaderPipeline object from inherited base classes: Pipeline with example: obj = COCOReaderPipeline(data_paths, batch_size, num_threads, shard_id, num_gpus, random_shuffle, stick_to_shard, shuffle_after_epoch, pad_last_batch, initial_fill)