code: def _make_ex(
      identifier: str, val_skew: str = "", val_noskew: str = ""
  ) -> tf.train.Example:
      """Makes an example with a skewed and unskewed feature."""
      ex = tf.train.Example()
      if identifier:
          ex.features.feature["id"].bytes_list.value.append(
              identifier.encode()
          )
      if val_skew:
          ex.features.feature["value_skew"].bytes_list.value.append(
              val_skew.encode()
          )
      if val_noskew:
          ex.features.feature["value_noskew"].bytes_list.value.append(
              val_noskew.encode()
          )
      return ex
  
imports: import traceback
  from absl.testing import absltest
  from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import tensorflow
  from tensorflow_data_validation.utils import beam_runner_util
  from tensorflow_data_validation.skew import feature_skew_detector
  from tensorflow_data_validation.skew.protos import feature_skew_results_pb2
  from tensorflow_data_validation.utils import test_util
  from google.protobuf import text_format
label_desc: Use image node_id 5 for calling a global function with example usage: _make_ex(identifier, val_skew, val_noskew) and returns: ex