class_docstr: This thread is responsible to download the chunks associated to a given worker.
code: def _maybe_delete_chunks(self) -> None:
      reached_pre_download = (
          self._pre_download_counter == self._max_pre_download
      )
  
      # we have already pre-downloaded some chunks, we just need to wait for them to be processed.
      chunk_index = _get_from_queue(
          self._to_delete_queue,
          timeout=_LONG_DEFAULT_TIMEOUT
          if reached_pre_download
          else _DEFAULT_TIMEOUT,
      )
  
      if chunk_index is not None:
          self._pre_download_counter -= 1
  
          # Store the current chunk index
          self._chunks_index_to_be_deleted.append(chunk_index)
  
      # Get the current cache size and decide whether we need to start cleanup. Otherwise, keep track of it
      while (
          self._max_cache_size
          and self._chunks_index_to_be_deleted
          and self._can_delete_chunk()
      ):
          # Delete the oldest chunk
          self._delete(self._chunks_index_to_be_deleted.pop(0))
  
      return
  
imports: import contextlib
  import multiprocessing
  import os
  import warnings
  from logging import Logger
  from queue import Empty
  from threading import Thread
  from typing import Any, Dict, List, Optional, Tuple, Union
  from lightning.data.streaming.config import ChunksConfig
  from lightning.data.streaming.constants import _TORCH_GREATER_EQUAL_2_1_0
  from lightning.data.streaming.item_loader import BaseItemLoader, PyTreeLoader
  from lightning.data.streaming.sampler import ChunkedIndex
  from lightning.data.streaming.serializers import Serializer, _get_serializers
  from lightning.data.utilities.env import _DistributedEnv, _WorkerEnv
label_desc: Use image node_id 6 for calling the PrepareChunksThread obj's underlying member method code with example usage: obj._maybe_delete_chunks() without return types