code: def __init__(
      self,
      data_paths,
      decoder_cache_params,
      shard_id,
      num_shards,
      random_shuffle,
      dont_use_mmap,
      **kwargs,
  ):
      super(WebdatasetPipeline, self).__init__(
          data_paths=data_paths,
          decoder_cache_params=decoder_cache_params,
          shard_id=shard_id,
          num_shards=num_shards,
          random_shuffle=random_shuffle,
          dont_use_mmap=dont_use_mmap,
          **kwargs,
      )
      wds, wds_idx = data_paths[:2]
  
      cache_enabled = decoder_cache_params["cache_enabled"]
      self.input = ops.readers.Webdataset(
          paths=wds,
          index_paths=wds_idx,
          ext=["jpg", "cls"],
          shard_id=shard_id,
          num_shards=num_shards,
          random_shuffle=random_shuffle,
          dont_use_mmap=dont_use_mmap,
          stick_to_shard=cache_enabled,
      )
  
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 WebdatasetPipeline object from inherited base classes: CommonPipeline with example: obj = WebdatasetPipeline(data_paths, decoder_cache_params, shard_id, num_shards, random_shuffle, dont_use_mmap)