code: def test_get_feature_value_slicer(self):
      features = {"a": None, "b": None}
      input_record_batch = pa.RecordBatch.from_arrays(
          [
              pa.array([[1], [2, 1], [3], [2, 1, 1], [3]]),
              pa.array(
                  [
                      ["dog"],
                      ["cat"],
                      ["wolf"],
                      ["dog", "wolf"],
                      ["wolf"],
                  ]
              ),
          ],
          ["a", "b"],
      )
      expected_result = [
          (
              "a_1_b_dog",
              pa.RecordBatch.from_arrays(
                  [
                      pa.array([[1], [2, 1, 1]]),
                      pa.array([["dog"], ["dog", "wolf"]]),
                  ],
                  ["a", "b"],
              ),
          ),
          (
              "a_1_b_cat",
              pa.RecordBatch.from_arrays(
                  [pa.array([[2, 1]]), pa.array([["cat"]])], ["a", "b"]
              ),
          ),
          (
              "a_2_b_cat",
              pa.RecordBatch.from_arrays(
                  [pa.array([[2, 1]]), pa.array([["cat"]])], ["a", "b"]
              ),
          ),
          (
              "a_2_b_dog",
              pa.RecordBatch.from_arrays(
                  [pa.array([[2, 1, 1]]), pa.array([["dog", "wolf"]])],
                  ["a", "b"],
              ),
          ),
          (
              "a_1_b_wolf",
              pa.RecordBatch.from_arrays(
                  [pa.array([[2, 1, 1]]), pa.array([["dog", "wolf"]])],
                  ["a", "b"],
              ),
          ),
          (
              "a_2_b_wolf",
              pa.RecordBatch.from_arrays(
                  [pa.array([[2, 1, 1]]), pa.array([["dog", "wolf"]])],
                  ["a", "b"],
              ),
          ),
          (
              "a_3_b_wolf",
              pa.RecordBatch.from_arrays(
                  [
                      pa.array([[3], [3]]),
                      pa.array([["wolf"], ["wolf"]]),
                  ],
                  ["a", "b"],
              ),
          ),
      ]
      self._check_results(
          slicing_util.get_feature_value_slicer(features)(
              input_record_batch
          ),
          expected_result,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import sys
  import unittest
  from absl.testing import absltest
  import apache_beam
  from apache_beam.testing import util
  import pyarrow
  from tensorflow_data_validation import constants
  from tensorflow_data_validation.utils import slicing_util
  from tfx_bsl.public.proto import slicing_spec_pb2
  from google.protobuf import text_format
label_desc: Use image node_id 2 for calling the SlicingUtilTest obj's underlying member method code with example usage: obj.test_get_feature_value_slicer() without return types