code: def test_train_and_eval(self, listwise_inference):
      tmp_dir = self.create_tempdir()
      data_file = os.path.join(tmp_dir, "elwc.tfrecord")
      if tf.io.gfile.exists(data_file):
          tf.io.gfile.remove(data_file)
  
      with tf.io.TFRecordWriter(data_file) as writer:
          for elwc in [ELWC] * 10:
              writer.write(elwc.SerializeToString())
  
      model_dir = os.path.join(tmp_dir, "model")
  
      with flagsaver.flagsaver(
          train_path=data_file,
          eval_path=data_file,
          data_format="example_list_with_context",
          model_dir=model_dir,
          num_train_steps=10,
          listwise_inference=listwise_inference,
          group_size=1,
          weights_feature_name="doc_weight",
      ):
          tf_ranking_tfrecord.train_and_eval()
  
file_path: ranking/tensorflow_ranking/examples/tf_ranking_tfrecord_test.py
imports: import os
  from absl import flags
  from absl.testing import flagsaver
  from absl.testing import parameterized
  import tensorflow
  from google.protobuf import text_format
  from tensorflow_ranking.examples import tf_ranking_tfrecord
  from tensorflow_serving.apis import input_pb2
label_desc: Use image node_id 1 for calling the TfRankingTFRecordTest obj's underlying member method code with example usage: obj.test_train_and_eval(listwise_inference) without return types