code: def test_int32_row_splits(self, row_splits_dtype):
      table = _create_table(_VOCAB)
      self.evaluate(table.initializer)
      tokenizer = bert_tokenizer.BertTokenizer(
          table,
          token_out_type=dtypes.string,
          lower_case=True,
          preserve_unused_token=False,
      )
  
      # Construct an input RaggedTensor [[b'candybook']]
      text_inputs = ragged_tensor.RaggedTensor.from_row_lengths(
          [b"candybook"], [1]
      )
      text_inputs = text_inputs.with_row_splits_dtype(row_splits_dtype)
  
      # The input had shape [1, 1] so the output will have shape
      # [1, 1, num_word_pieces], where num_word_pieces=2.
      results = tokenizer.tokenize(text_inputs)
  
      # Check that the row_splits dtypes for the input and output tensors match.
      self.assertEqual(results.row_splits.dtype, row_splits_dtype)
  
      # Verify that the output values are correct (sanity check).
      self.assertAllEqual(results.flat_values, [b"candy", b"##book"])
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import lookup_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_map_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import test
  from tensorflow_text.python.ops import bert_tokenizer
label_desc: Use image node_id 4 for calling the BertTokenizerTest obj's underlying member method code with example usage: obj.test_int32_row_splits(row_splits_dtype) without return types