code: def test_model_fn_binary_class(
      self, problem, input_shape, label_vocabulary, labels_fn, hparams
  ):
      num_classes = 2
      loss_fn = loss_fns.make_multi_class_loss_fn(
          label_vocabulary=label_vocabulary
      )
      instance = self._create_phoenix_instance(
          problem_type=problem,
          input_shape=input_shape,
          logits_dimension=num_classes,
          label_vocabulary=label_vocabulary,
          loss_fn=loss_fn,
      )
      run_config = tf.estimator.RunConfig(
          model_dir=self.get_temp_dir() + "/1"
      )
  
      def input_fn():
          features = {"zeros": tf.zeros(input_shape)}
          labels = labels_fn()
          return features, labels
  
      estimator = instance.get_estimator(run_config, hparams, 10)
      estimator.train(input_fn=input_fn, max_steps=10)
      eval_result = estimator.evaluate(input_fn=input_fn, steps=10)
  
      self.assertIn("auc_roc", eval_result)
  
imports: import os
  from absl import flags
  from absl.testing import parameterized
  from model_search import hparam
  from model_search import loss_fns
  from model_search import phoenix
  from model_search.architecture import architecture_utils
  from model_search.metadata import mock_metadata
  from model_search.proto import phoenix_spec_pb2
  import numpy
  import tensorflow.compat.v2
  from google.protobuf import text_format
label_desc: Use image node_id 12 for calling the PhoenixTest obj's underlying member method code with example usage: obj.test_model_fn_binary_class(problem, input_shape, label_vocabulary, labels_fn, hparams) and returns: features,  labels