code: def load_from_indices(self, indices, verbose=False):
      (
          chunk_arr,
          chunk_sub_index_arr,
      ) = self.chunker.lookup_chunk_and_index(indices)
      reverse_index = np.arange(len(indices)).astype(int)
      result = [None] * len(indices)
      for chunk_i in sorted(list(set(chunk_arr))):
          selector = chunk_arr == chunk_i
          chunk = self.load_chunk(chunk_i)
          selected_chunk_sub_index_arr = chunk_sub_index_arr[selector]
          selected_reverse_index = reverse_index[selector]
          if verbose:
              print(
                  f"Loading {len(selected_chunk_sub_index_arr)} indices from chunk {chunk_i}"
              )
          for i, j in zip(
              selected_chunk_sub_index_arr, selected_reverse_index
          ):
              result[j] = chunk[i]
          del chunk
      return result
  
imports: import math
  import numpy
  import os
  from typing import Generator, Union, Sequence
  import torch
  import torch.utils.data.dataset
label_desc: Use image node_id 5 for calling the ChunkedFilesDataCache obj's underlying member method code with example usage: obj.load_from_indices(indices, verbose) and returns: result