code: def get_neighbor_tokens(cls, sample_id, chunk_id, data_key="train"):
      try:
          sample = cls.get_pt_sample(data_key, sample_id)
          sample_token_ids = sample["text"]
          chunk_length = cls.args.retro_gpt_chunk_length
          chunk_start_idx = chunk_id * chunk_length
          chunk_end_idx = min(
              sample_token_ids.shape[0], chunk_start_idx + chunk_length
          )
          chunk_token_ids = sample_token_ids[
              chunk_start_idx:chunk_end_idx
          ]
          neighbor_token_ids = sample["neighbor_tokens"][chunk_id]
          return {
              "chunk_tokens": chunk_token_ids,
              "neighbor_tokens": neighbor_token_ids,
          }
      except:
          return None
  
imports: import json
  import numpy
  import os
  import torch
  import types
  from megatron.global_vars import set_global_variables, set_retro_args
  from megatron.initialize import initialize_megatron, _initialize_distributed, _set_random_seed, _compile_dependencies
  from tools.retro.db.utils import get_indexed_dataset_infos, get_merged_train_dataset
  from tools.retro.main import add_retro_args
  from tools.retro.query.retro_dataset import get_retro_datasets
  from tools.retro.utils import get_args_path, get_bert_tokenizer, get_gpt_tokenizer
label_desc: Use image node_id 19 for calling the retro obj's underlying member method code with example usage: obj.get_neighbor_tokens(cls, sample_id, chunk_id, data_key) and returns: dict, None