code: def load_item_from_chunk(
      self,
      index: int,
      chunk_index: int,
      chunk_filepath: str,
      begin: int,
  ) -> torch.Tensor:
      if (
          chunk_filepath in self._chunk_filepaths
          and not os.path.isfile(chunk_filepath)
      ):
          del self._chunk_filepaths[chunk_filepath]
  
      if chunk_filepath not in self._chunk_filepaths:
          first_exists = exists = os.path.exists(chunk_filepath)
  
          while not exists:
              sleep(0.1)
              exists = os.path.exists(chunk_filepath)
  
          # Wait to avoid any corruption when the file appears
          if not first_exists:
              sleep(0.001)
  
          self._chunk_filepaths[chunk_filepath] = True
  
      self._load_chunk(chunk_index, chunk_filepath)
      assert self._dtype
  
      buffer: bytes = self._buffers[chunk_index]
      offset = self._dtype.itemsize * (index - begin) * self._block_size
      return torch.frombuffer(
          buffer,
          dtype=self._dtype,
          count=self._block_size,
          offset=offset,
      )
  
imports: import os
  from abc import ABC, abstractmethod
  from time import sleep
  from typing import Any, Dict, List, Optional, Tuple
  import numpy
  import torch
  from lightning.data.streaming.constants import _TORCH_DTYPES_MAPPING, _TORCH_GREATER_EQUAL_2_1_0
  from lightning.data.streaming.serializers import Serializer
label_desc: Use image node_id 7 for calling the TokensLoader obj's underlying member method code with example usage: obj.load_item_from_chunk(index, chunk_index, chunk_filepath, begin) and returns: torch