code: def _create_cache(self, worker_env: _WorkerEnv) -> Cache:
      env = Environment(
          dist_env=self.distributed_env, worker_env=worker_env
      )
  
      cache_dir = os.path.join(self.input_dir.path, str(env.shard_rank))
      os.makedirs(cache_dir, exist_ok=True)
  
      cache = Cache(
          input_dir=Dir(cache_dir, self.input_dir.url),
          item_loader=self.item_loader,
          chunk_bytes=1,
          serializers=self.serializers,
      )
      cache._reader._try_load_config()
  
      if not cache.filled:
          raise ValueError(
              f"The provided dataset `{self.input_dir}` doesn't contain any {_INDEX_FILENAME} file."
              " HINT: Did you successfully optimize a dataset to the provided `input_dir`?"
          )
  
      return cache
  
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 1 for calling the EmulateS3StreamingDataset obj's underlying member method code with example usage: obj._create_cache(worker_env) and returns: cache