code: def testVectorSingleValueTokenAcrossSpace(self):
      test_string = b"I love Flume!"
      test_strings = constant_op.constant([test_string])
  
      # Below, each pair of logits [l1, l2] indicates a "split" action
      # if l1 < l2 and a "merge" otherwise.
      test_logits = constant_op.constant(
          [
              [
                  # I
                  [2.7, -0.3],  # I: split
                  # ' '
                  [-1.5, 2.3],  # <space>: merge
                  # love
                  [4.1, 0.82],  # l: split
                  [-2.3, 4.3],  # o: merge
                  [3.1, 12.2],  # v: merge
                  [-3.0, 4.7],  # e: merge
                  # ' '
                  [2.5, 32.0],  # <space>: merge
                  # Flume
                  [-2.7, 5.3],  # F: merge
                  [0.7, 15.0],  # l: merge
                  [1.6, 23.0],  # u: merge
                  [2.1, 11.0],  # m: merge
                  [0.0, 20.0],  # e: merge
                  # !
                  [18.0, 0.7],  # !: split
              ]
          ]
      )
  
      # 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_start_offsets = [[0, 2, 7, 12]]
      expected_end_offsets = [[1, 6, 12, 13]]
      (tokens, starts, ends) = self.tokenizer.tokenize_with_offsets(
          test_strings, test_logits
      )
      self.assertAllEqual(expected_tokens, tokens)
      self.assertAllEqual(expected_start_offsets, starts)
      self.assertAllEqual(expected_end_offsets, ends)
  
      # Use the same arguments to test the tokenize() version, without offsets.
      tokens = self.tokenizer.tokenize(test_strings, test_logits)
      self.assertAllEqual(expected_tokens, 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_start_offsets = [[0, 2, 12]]
      expected_end_offsets = [[1, 12, 13]]
      # Assertions below clarify what the expected offsets mean:
      self.assertEqual(b"I", test_string[0:1])
  
      # 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(b"love Flume", test_string[2:12])
      self.assertEqual(b"!", test_string[12:13])
  
      (
          tokens,
          starts,
          ends,
      ) = self.no_force_split_tokenizer.tokenize_with_offsets(
          test_strings, test_logits
      )
      self.assertAllEqual(expected_tokens, tokens)
      self.assertAllEqual(expected_start_offsets, starts)
      self.assertAllEqual(expected_end_offsets, ends)
  
      # Use the same arguments to test the tokenize() version, without offsets.
      tokens = self.no_force_split_tokenizer.tokenize(
          test_strings, test_logits
      )
      self.assertAllEqual(expected_tokens, 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 errors
  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_tensor
  from tensorflow.python.platform import test
  from tensorflow_text.python.ops.split_merge_from_logits_tokenizer import SplitMergeFromLogitsTokenizer
label_desc: Use image node_id 3 for calling the SplitMergeFromLogitsTokenizerTest obj's underlying member method code with example usage: obj.testVectorSingleValueTokenAcrossSpace() without return types