code: def __iter__(self):
      seen = 0
      buffer_chunked_indices = self.get_buffer_chunked_indices()
      for buffer_chunked_index in buffer_chunked_indices:
          if self.verbose:
              print(
                  f"Loading buffer {seen} - {seen + len(buffer_chunked_index)}"
                  f" out of {len(self)}"
              )
          buffer = self.chunked_file_data_cache.load_from_indices(
              buffer_chunked_index, verbose=self.verbose
          )
          for elem in buffer:
              yield elem
          seen += len(buffer_chunked_index)
  
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 2 for calling the ChunkedFilesIterableDataset obj's underlying member method code with example usage: obj.__iter__() without return types