code: def _get_tokens(s):
      """get normalized tokens for both Chinese and English"""
      if not s:
          return []
  
      # separate answers to en and ch pieces
      ch_seq = ""
      en_seq = ""
      pos = 0
  
      # Normalize and connect
      final_tokens = []
  
      while pos < len(s):
          if check_chinese_char(s[pos]):
              if en_seq != "":
                  final_tokens.extend(normalize_answer(en_seq).split())
                  en_seq = ""
              ch_seq += s[pos]
          else:
              if ch_seq != "":
                  final_tokens.extend(normalize_chinese_answer(ch_seq))
                  ch_seq = ""
              en_seq += s[pos]
          pos += 1
  
      if en_seq != "":
          final_tokens.extend(normalize_answer(en_seq).split())
  
      if ch_seq != "":
          final_tokens.extend(normalize_chinese_answer(ch_seq))
  
      return final_tokens
  
imports: import collections
  from typing import List
  import ijson
  import numpy
  from transformers.models.bert.tokenization_bert import BasicTokenizer
  from nemo.collections.nlp.data.data_utils import DataProcessor, check_chinese_char, normalize_answer, normalize_chinese_answer
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: _get_tokens(s) and returns: final_tokens, list