code: def test_unicode_tokenization_in_text_vec(self):
      input_data = [[b"I love Flume!"]]
      expected_output = [[b"i", b"love", b"flume"]]
      if not tf.executing_eagerly() and not isinstance(
          input_data, np.ndarray
      ):
          # In TF1 list-of-lists-of-scalars need to be wrapped in an extra list
          # for single-io models, because it tries to disambiguate which
          # input to send an input to (which causes issues w/ single io models)
          input_data = [input_data]
  
      # create a functional API model
      i = tf.keras.layers.Input(shape=(1,), dtype=tf.string)
      splitter = tokenization_layers.UnicodeScriptTokenizer()
      layer = tf.keras.layers.TextVectorization(
          split=splitter, output_mode=None
      )
      o = layer(i)
      model = tf.keras.models.Model(i, o)
  
      # evaluate the model
      self.assertAllEqual(model.predict(input_data), expected_output)
  
file_path: text/tensorflow_text/python/keras/layers/tokenization_layers_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_text.python.keras.layers import tokenization_layers
label_desc: Use image node_id 4 for calling the TokenizationLayersTest obj's underlying member method code with example usage: obj.test_unicode_tokenization_in_text_vec() without return types