code: def test_dataset_for_text_tokens_distributed_num_workers_end_to_end(
      tmpdir, monkeypatch
  ):
      monkeypatch.setattr(
          functions, "_get_input_dir", lambda x: str(tmpdir)
      )
  
      seed_everything(42)
  
      with open(tmpdir / "a.txt", "w") as f:
          f.write("hello")
  
      inputs = [(v, str(tmpdir / "a.txt")) for v in range(0, 200, 20)]
  
      cache_dir = os.path.join(tmpdir, "cache")
      output_dir = os.path.join(tmpdir, "target_dir")
      os.makedirs(output_dir, exist_ok=True)
      monkeypatch.setenv("DATA_OPTIMIZER_CACHE_FOLDER", cache_dir)
      monkeypatch.setenv("DATA_OPTIMIZER_DATA_CACHE_FOLDER", cache_dir)
  
      functions.optimize(
          optimize_fn,
          inputs,
          output_dir=str(tmpdir),
          num_workers=2,
          chunk_size=2,
          reorder_files=False,
          num_downloaders=1,
      )
  
      assert (
          len([f for f in os.listdir(tmpdir) if f.endswith(".bin")])
          == 10
      )
  
      block_size = 10
      dataset = StreamingDataset(
          input_dir=str(tmpdir),
          item_loader=TokensLoader(block_size),
          shuffle=False,
      )
  
      L = len(dataset)
      assert len(dataset) == L
  
      for i in range(L):
          sequence = dataset[i]
          assert sequence[0].item() == i * block_size
          assert sequence[-1].item() == (i + 1) * block_size - 1
  
      dataset = StreamingDataset(
          input_dir=str(tmpdir),
          item_loader=TokensLoader(block_size),
          shuffle=False,
      )
  
      dataset.distributed_env = _DistributedEnv(2, 0)
      dataloader = DataLoader(
          dataset, batch_size=2, shuffle=False, num_workers=2
      )
  
      assert len(dataloader) == 5
  
      expected = [[0, 10], [40, 50], [80, 90], [120, 130], [160, 170]]
  
      for batch_idx, batch in enumerate(dataloader):
          assert [batch[0][0].item(), batch[1][0].item()] == expected[
              batch_idx
          ]
  
      dataset.distributed_env = _DistributedEnv(2, 1)
      dataloader = DataLoader(dataset, batch_size=2, shuffle=False)
  
      assert len(dataloader) == 5
  
      expected = [
          [20, 30],
          [60, 70],
          [100, 110],
          [140, 150],
          [180, 190],
      ]
  
      for batch_idx, batch in enumerate(dataloader):
          assert [batch[0][0].item(), batch[1][0].item()] == expected[
              batch_idx
          ]
  
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 13 for calling a global function with example usage: test_dataset_for_text_tokens_distributed_num_workers_end_to_end(tmpdir, monkeypatch) without return types