code: def testVectorSingleValueTokenCrossSpace(self):
      test_string = b"I love Flume!"
      test_value = constant_op.constant([test_string])
      test_label = constant_op.constant(
          [
              [
                  # I
                  0,
                  # ' '
                  1,
                  # love
                  0,
                  1,
                  1,
                  1,
                  # ' '
                  0,
                  # Flume
                  1,
                  1,
                  1,
                  1,
                  1,
                  # !
                  0,
              ]
          ]
      )
  
      # By default force_split_at_break_character is set True, so we start new
      # tokens after break characters regardless of the SPLIT/MERGE label of the
      # break character.
      expected_tokens = [[b"I", b"love", b"Flume", b"!"]]
      expected_offset_starts = [[0, 2, 7, 12]]
      expected_offset_ends = [[1, 6, 12, 13]]
      (tokens, starts, ends) = self.tokenizer.tokenize_with_offsets(
          test_value, test_label
      )
      self.assertAllEqual(tokens, expected_tokens)
      self.assertAllEqual(starts, expected_offset_starts)
      self.assertAllEqual(ends, expected_offset_ends)
  
      # Use the same arguments to test the tokenize() version, without offsets.
      tokens = self.tokenizer.tokenize(test_value, test_label)
      self.assertAllEqual(tokens, expected_tokens)
  
      # When force_split_at_break_character set false, we may combine two tokens
      # together to form a word according to the label of the first non-space
      # character.
      expected_tokens = [[b"I", b"loveFlume", b"!"]]
      expected_offset_starts = [[0, 2, 12]]
      expected_offset_ends = [[1, 12, 13]]
      # Assertions below clarify what the expected offsets mean:
      self.assertEqual(test_string[0:1], b"I")
  
      # Notice that the original text between the [start, end) offsets for the
      # second token differs from the token text by an extra space: this is
      # by design, that space is not copied in the token.
      self.assertEqual(test_string[2:12], b"love Flume")
      self.assertEqual(test_string[12:13], b"!")
  
      (tokens, starts, ends) = self.tokenizer.tokenize_with_offsets(
          test_value, test_label, force_split_at_break_character=False
      )
      self.assertAllEqual(tokens, expected_tokens)
      self.assertAllEqual(starts, expected_offset_starts)
      self.assertAllEqual(ends, expected_offset_ends)
  
      # Use the same arguments to test the tokenize() version, without offsets.
      tokens = self.tokenizer.tokenize(
          test_value, test_label, force_split_at_break_character=False
      )
      self.assertAllEqual(tokens, expected_tokens)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow_text.python.ops.split_merge_tokenizer import SplitMergeTokenizer
label_desc: Use image node_id 4 for calling the SplitMergeTokenizerTest obj's underlying member method code with example usage: obj.testVectorSingleValueTokenCrossSpace() without return types