code: def test_streaming_dataset_deepcopy(tmpdir):
      seed_everything(42)
  
      remote_dir = os.path.join(tmpdir, "remote_dir")
  
      os.makedirs(remote_dir, exist_ok=True)
  
      cache = Cache(remote_dir, chunk_size=10)
      for i in range(10):
          cache[i] = i
  
      cache.done()
      cache.merge()
  
      dataset = StreamingDataset(input_dir=remote_dir, shuffle=True)
      assert dataset.cache is None
      iter(dataset)
      assert dataset.cache is not None
      assert dataset.cache._reader._prepare_thread is None
      dataset.cache._reader._prepare_thread = True
      dataloader = DataLoader(dataset, num_workers=1)
  
      batches = []
      for batch in dataloader:
          batches.append(batch)
  
      assert len(batches) == 10
  
imports: import os
  import sys
  from time import sleep
  from unittest import mock
  import numpy
  import pytest
  import torch
  from lightning import seed_everything
  from lightning.data.streaming import Cache, functions
  from lightning.data.streaming.dataloader import StreamingDataLoader
  from lightning.data.streaming.dataset import _INDEX_FILENAME, Dir, RemoteDir, StreamingDataset, _associate_chunks_to_workers, _replay_chunks_sampling, _replay_sampling, _should_replace_path, _try_create_cache_dir
  from lightning.data.streaming.item_loader import TokensLoader
  from lightning.data.streaming.shuffle import FullShuffle, NoShuffle
  from lightning.data.utilities.env import Environment, _DistributedEnv, _WorkerEnv
  from torch.utils.data import DataLoader
label_desc: Use image node_id 6 for calling a global function with example usage: test_streaming_dataset_deepcopy(tmpdir) without return types