docstr: The ChunksConfig reads the index files associated a chunked dataset and enables to map an index to its
  chunk.
  
  Arguments:
      cache_dir: The path to cache folder.
      serializers: The serializers used to serialize and deserialize the chunks.
      remote_dir: The path to a remote folder where the data are located.
          The scheme needs to be added to the path.
docstr_tok: ["The","ChunksConfig","reads","the","index","files","associated","a","chunked","dataset","and","enables","to","map","an","index","to","its","chunk",".","Arguments",":","cache_dir",":","The","path","to","cache","folder",".","serializers",":","The","serializers","used","to","serialize","and","deserialize","the","chunks",".","remote_dir",":","The","path","to","a","remote","folder","where","the","data","are","located",".","The","scheme","needs","to","be","added","to","the","path","."]
code: def __init__(
      self,
      cache_dir: str,
      serializers: Dict[str, Serializer],
      remote_dir: Optional[str],
      item_loader: Optional[BaseItemLoader] = None,
  ) -> None:
      """The ChunksConfig reads the index files associated a chunked dataset and enables to map an index to its
      chunk.
  
      Arguments:
          cache_dir: The path to cache folder.
          serializers: The serializers used to serialize and deserialize the chunks.
          remote_dir: The path to a remote folder where the data are located.
              The scheme needs to be added to the path.
  
      """
      self._cache_dir = cache_dir
      self._intervals: List[Tuple[int, int]] = []
      self._config = None
      self._chunks = []
      self._remote_dir = remote_dir
      self._item_loader = item_loader or PyTreeLoader()
  
      with open(os.path.join(self._cache_dir, _INDEX_FILENAME)) as f:
          data = json.load(f)
          self._config = data["config"]
          self._validate_item_loader()
          self._chunks.extend(data["chunks"])
  
      self._config["data_spec"] = treespec_loads(
          self._config["data_spec"]
      )
  
      self._item_loader.setup(self._config, self._chunks, serializers)
      self._intervals = self._item_loader.generate_intervals()
      self._length = self._intervals[-1][-1]
      self._downloader = None
  
      if remote_dir:
          self._downloader = get_downloader_cls(
              remote_dir, cache_dir, self._chunks
          )
  
imports: import json
  import os
  from typing import Any, Dict, List, Optional, Tuple
  from lightning.data.streaming.constants import _INDEX_FILENAME, _TORCH_GREATER_EQUAL_2_1_0
  from lightning.data.streaming.downloader import get_downloader_cls
  from lightning.data.streaming.item_loader import BaseItemLoader, PyTreeLoader, TokensLoader
  from lightning.data.streaming.sampler import ChunkedIndex
  from lightning.data.streaming.serializers import Serializer
label_desc: Use image node_id 1 to create a new ChunksConfig object  with example: obj = ChunksConfig(cache_dir, serializers, remote_dir, item_loader)