code: def _OriginalNormalize(text_input, lower_case_nfd_strip_accents):
      """Based on tensorflow_text/python/ops/bert_tokenizer.py.
  
      Args:
        text_input: the input tensor.
        lower_case_nfd_strip_accents: bool - If true, a preprocessing step is added
          to lowercase the text, which also applies NFD normalization and strips
          accents from characters.
  
      Returns:
        The normalized text.
      """
      if lower_case_nfd_strip_accents:
          text_input = normalize_ops.case_fold_utf8(text_input)
          text_input = normalize_ops.normalize_utf8(text_input, "NFD")
          text_input = string_ops.regex_replace(
              text_input, r"\p{Mn}", ""
          )
      # strip out control characters
      text_input = string_ops.regex_replace(
          text_input, r"\p{Cc}|\p{Cf}", " "
      )
      return text_input
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_text
  from tensorflow.lite.python import interpreter
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
  from tensorflow_text.core.pybinds import pywrap_fast_bert_normalizer_model_builder
  from tensorflow_text.python.ops import fast_bert_normalizer
  from tensorflow_text.python.ops import normalize_ops
label_desc: Use image node_id 2 for calling a global function with example usage: _OriginalNormalize(text_input, lower_case_nfd_strip_accents) and returns: text_input