code: def test_single_sample_and_junk():
      test_batch_size = 1
      num_samples = 1
      tar_file_path = os.path.join(
          get_dali_extra_path(),
          "db/webdataset/sample-tar/single_junk.tar",
      )
      index_file = base.generate_temp_index_file(tar_file_path)
  
      extract_dir = base.generate_temp_extract(tar_file_path)
      equivalent_files = list(sorted(glob(extract_dir.name + "/*")))
  
      compare_pipelines(
          base.webdataset_raw_pipeline(
              tar_file_path,
              index_file.name,
              ["txt"],
              batch_size=test_batch_size,
              device_id=0,
              num_threads=1,
          ),
          base.file_reader_pipeline(
              equivalent_files,
              ["txt"],
              batch_size=test_batch_size,
              device_id=0,
              num_threads=1,
          ),
          test_batch_size,
          math.ceil(num_samples / test_batch_size) * 10,
      )
      wds_pipeline = base.webdataset_raw_pipeline(
          tar_file_path,
          index_file.name,
          ["txt"],
          batch_size=test_batch_size,
          device_id=0,
          num_threads=1,
      )
      wds_pipeline.build()
      assert_equal(
          list(wds_pipeline.epoch_size().values())[0], num_samples
      )
  
file_path: DALI/dali/test/python/reader/test_webdataset_corner.py
imports: import math
  import nvidia.dali
  import os
  import tempfile
  from glob import glob
  from nose.tools import assert_equal
  import webdataset_base
  from nose_utils import assert_raises
  from test_utils import compare_pipelines, get_dali_extra_path
label_desc: Use image node_id 6 for calling a global function with example usage: test_single_sample_and_junk() without return types