code: def test_cache_for_image_dataset_distributed(num_workers, tmpdir):
      cache_dir = os.path.join(tmpdir, "cache")
      os.makedirs(cache_dir)
  
      fabric = Fabric(
          accelerator="cpu", devices=2, strategy="ddp_spawn"
      )
      fabric.launch(
          partial(
              _fabric_cache_for_image_dataset,
              num_workers=num_workers,
              tmpdir=tmpdir,
          )
      )
  
imports: import json
  import os
  import sys
  from functools import partial
  import numpy
  import pytest
  import torch
  from lightning import seed_everything
  from lightning.data.streaming import Cache
  from lightning.data.streaming.dataloader import CacheDataLoader
  from lightning.data.streaming.dataset import StreamingDataset
  from lightning.data.streaming.item_loader import TokensLoader
  from lightning.data.streaming.serializers import Serializer
  from lightning.data.utilities.env import _DistributedEnv
  from lightning.fabric import Fabric
  from lightning.pytorch.demos.boring_classes import RandomDataset
  from lightning_utilities.core.imports import RequirementCache
  from lightning_utilities.test.warning import no_warning_call
  from torch.utils.data import Dataset
label_desc: Use image node_id 4 for calling a global function with example usage: test_cache_for_image_dataset_distributed(num_workers, tmpdir) without return types