code: def basic_tokenizer(
      sentence, _WORD_SPLIT=re.compile(b"([.,!?\"':;)(])")
  ):
      """Very basic tokenizer: split the sentence into a list of tokens.
  
      Parameters
      -----------
      sentence : tensorflow.python.platform.gfile.GFile Object
      _WORD_SPLIT : regular expression for word spliting.
  
  
      Examples
      --------
      >>> see create_vocabulary
      >>> from tensorflow.python.platform import gfile
      >>> train_path = "wmt/giga-fren.release2"
      >>> with gfile.GFile(train_path + ".en", mode="rb") as f:
      >>>    for line in f:
      >>>       tokens = tl.nlp.basic_tokenizer(line)
      >>>       tl.logging.info(tokens)
      >>>       exit()
      [b'Changing', b'Lives', b'|', b'Changing', b'Society', b'|', b'How',
        b'It', b'Works', b'|', b'Technology', b'Drives', b'Change', b'Home',
        b'|', b'Concepts', b'|', b'Teachers', b'|', b'Search', b'|', b'Overview',
        b'|', b'Credits', b'|', b'HHCC', b'Web', b'|', b'Reference', b'|',
        b'Feedback', b'Virtual', b'Museum', b'of', b'Canada', b'Home', b'Page']
  
      References
      ----------
      - Code from ``/tensorflow/models/rnn/translation/data_utils.py``
  
      """
      words = []
      sentence = as_bytes(sentence)
      for space_separated_fragment in sentence.strip().split():
          words.extend(re.split(_WORD_SPLIT, space_separated_fragment))
      return [w for w in words if w]
  
imports: import collections
  import os
  import random
  import re
  import subprocess
  import tempfile
  import warnings
  from collections import Counter
  import numpy
  import six
  import tensorflow
  from six.moves import urllib, xrange
  from tensorflow.python.platform import gfile
  import tensorlayer
  from tensorlayer.lazy_imports import LazyImport
label_desc: Use image node_id 17 for calling a global function with example usage: basic_tokenizer(sentence, _WORD_SPLIT) and returns: unknown