code: def _split_sentences(s1, s2):
      s1 = text_encoder.native_to_unicode(s1)
      s2 = text_encoder.native_to_unicode(s2)
      s1 = re.sub(
          r"(\w[A-Z]|[0-9a-z])([.!?]) ([A-Z])", r"\1\2__|__\3", s1
      )
      s2 = re.sub(r"([^0-9][.!?]) ([A-Z])", r"\1__|__\2", s2)
      s1_subsentences = s1.split("__|__")
      s2_subsentences = s2.split("__|__")
      return s1_subsentences, s2_subsentences
  
file_path: tensor2tensor/tensor2tensor/data_generators/cleaner_en_xx.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import itertools
  import re
  from tensor2tensor.data_generators import text_encoder
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling a global function with example usage: _split_sentences(s1, s2) and returns: s1_subsentences,  s2_subsentences