code: def nosep_getitem_fixed(self, i):
      if i > self.data_creator.len:
          raise IndexError
      if i < 0:
          i += self.data_creator.len
      instance_start, instance_end = self.data_creator.instance_offsets[
          i : i + 2
      ]
      (
          tok_offsets_start,
          tok_offsets_end,
      ) = self.data_creator.instance_token_offsets[i : i + 2]
      token_offsets = self.data_creator.token_offsets[
          tok_offsets_start:tok_offsets_end
      ]
      tokens_split = self.data_creator.tokens_split[i]
      token_arrs = np.split(
          self.data_creator.data[instance_start:instance_end],
          token_offsets,
      )
      tokens = [t.tostring().decode("utf8") for t in token_arrs]
  
      return (
          tokens[:tokens_split],
          tokens[tokens_split:],
          self.data_creator.is_next[i],
      )
  
imports: from tqdm import tqdm
  from typing import Tuple
  from random import shuffle
  import pickle
  import random
  import numpy
  from pathlib import Path
  from pytorch_pretrained_bert.tokenization import BertTokenizer
label_desc: Use image node_id 5 for calling the NumpyByteInstances obj's underlying member method code with example usage: obj.nosep_getitem_fixed(i) and returns: tokens,  tokens,  self