code: def testSliceOneSlice(self):
      with beam.Pipeline() as pipeline:
          fpls = create_fpls()
          metrics = (
              pipeline
              | "CreateTestInput" >> beam.Create(fpls, reshuffle=False)
              | "WrapFpls" >> beam.Map(wrap_fpl)
              | "ExtractSlices"
              >> slice_key_extractor.ExtractSliceKeys(
                  [
                      slicer.SingleSliceSpec(),
                      slicer.SingleSliceSpec(columns=["gender"]),
                  ]
              )
              | "FanoutSlices" >> slicer.FanoutSlices()
          )
  
          def check_result(got):
              try:
                  self.assertLen(got, 4)
                  expected_result = [
                      ((), wrap_fpl(fpls[0])),
                      ((), wrap_fpl(fpls[1])),
                      ((("gender", "f"),), wrap_fpl(fpls[0])),
                      ((("gender", "m"),), wrap_fpl(fpls[1])),
                  ]
                  self.assertCountEqual(got, expected_result)
              except AssertionError as err:
                  raise util.BeamAssertException(err)
  
          util.assert_that(metrics, check_result)
  
imports: from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import six
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.extractors import slice_key_extractor
  from tensorflow_model_analysis.post_export_metrics import metric_keys
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
  from tensorflow_model_analysis.slicer import slicer_lib
  from google.protobuf import text_format
label_desc: Use image node_id 21 for calling the SlicerTest obj's underlying member method code with example usage: obj.testSliceOneSlice() without return types