code: def tokenize_lines_fn(x):
      """
      Worker function to tokenize lines based on the tokenizer, and perform vocabulary lookup.
  
      Parameters
      ----------
      lines
          Lines to be tokenized of the whole file
      tokenizer
          The trained tokenizer
  
      Returns
      -------
      results
          A list storing the valid tokenized lines
      """
      lines, tokenizer = x
      results = []
      for line in lines:
          if not line:
              break
          line = line.strip()
          # Empty lines are used as document delimiters
          if not line:
              results.append([])
          else:
              token_ids = tokenizer.encode(line, int)
              if token_ids:
                  results.append(token_ids)
      return results
  
imports: import argparse
  import logging
  import io
  import os
  import glob
  import collections
  import warnings
  import random
  import time
  from multiprocessing import Pool
  import numpy
  from gluonnlp.models.bert import BertModel, BertForPretrain, get_pretrained_bert
  import gluonnlp
label_desc: Use image node_id 4 for calling a global function with example usage: tokenize_lines_fn(x) and returns: results