code: def _create_pipeline(self, loss_key):
      hparams = _make_hparams(
          train_input_pattern=self._data_file,
          eval_input_pattern=self._data_file,
          model_dir=self._model_dir,
          list_size=5,
          loss_key=loss_key,
      )
      estimator = tfr.estimator.EstimatorBuilder(
          _context_feature_columns(),
          _example_feature_columns(),
          _scoring_function,
          hparams=hparams,
      ).make_estimator()
      return pipeline.RankingPipeline(
          _context_feature_columns(),
          _example_feature_columns(),
          hparams=hparams,
          estimator=estimator,
          label_feature_name="utility",
          label_feature_type=tf.float32,
      )
  
imports: import os
  from absl.testing import parameterized
  import tensorflow
  from tensorflow import estimator
  import tensorflow_ranking
  from google.protobuf import text_format
  from tensorflow_ranking.extension import pipeline
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 3 for calling the RankingPipelineTest obj's underlying member method code with example usage: obj._create_pipeline(loss_key) and returns: pipeline