code: def read_and_check_instances(
      self, filepath: str, num_workers: int = 0
  ):
      data_loader = MultiProcessDataLoader(
          self.reader,
          filepath,
          num_workers=num_workers,
          batch_size=1,
          start_method="spawn",
      )
      all_instances = []
      for instance in data_loader.iter_instances():
          all_instances.append(instance)
  
      # 100 files * 4 sentences / file
      assert len(all_instances) == 100 * 4
  
      counts = Counter(
          fingerprint(instance) for instance in all_instances
      )
  
      # should have the exact same data 100 times
      assert len(counts) == 4
      assert (
          counts[("cats", "are", "animals", ".", "N", "V", "N", "N")]
          == 100
      )
      assert (
          counts[("dogs", "are", "animals", ".", "N", "V", "N", "N")]
          == 100
      )
      assert (
          counts[("snakes", "are", "animals", ".", "N", "V", "N", "N")]
          == 100
      )
      assert (
          counts[("birds", "are", "animals", ".", "N", "V", "N", "N")]
          == 100
      )
  
file_path: allennlp/tests/data/dataset_readers/sharded_dataset_reader_test.py
imports: import glob
  import os
  import tarfile
  from collections import Counter
  from typing import Tuple
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.data.data_loaders import MultiProcessDataLoader
  from allennlp.data.dataset_readers import SequenceTaggingDatasetReader, ShardedDatasetReader
  from allennlp.data.instance import Instance
label_desc: Use image node_id 2 for calling the TestShardedDatasetReader obj's underlying member method code with example usage: obj.read_and_check_instances(filepath, num_workers) without return types