code: def __init__(self, args, data_path=test_data_path):
      super(COCODetectionPipeline, self).__init__(
          args.batch_size, args.num_workers, 0, 0
      )
  
      self.input = ops.readers.COCO(
          file_root=os.path.join(data_path, "images"),
          annotations_file=os.path.join(data_path, "instances.json"),
          shard_id=0,
          num_shards=1,
          ratio=True,
          ltrb=True,
          random_shuffle=False,
      )
  
      self.decode_gpu = ops.decoders.Image(
          device="mixed", output_type=types.RGB
      )
      self.box_encoder = ops.BoxEncoder(
          device="cpu", criteria=0.5, anchors=coco_anchors()
      )
  
file_path: DALI/dali/test/python/test_coco_tfrecord.py
imports: import argparse
  import os
  import nvidia.dali.ops
  import nvidia.dali.types
  from nvidia.dali.pipeline import Pipeline
  import nvidia.dali.tfrecord
  from test_detection_pipeline import coco_anchors
  from test_utils import compare_pipelines, get_dali_extra_path
label_desc: Use image node_id 1 to create a new COCODetectionPipeline object from inherited base classes: Pipeline with example: obj = COCODetectionPipeline(args, data_path)