from tensorflow.contrib.layers.python.layers import feature_column

    self._assertSingleClassMetrics(metrics)

  def benchmarkCustomOptimizer(self):
    iris = test_data.prepare_iris_data_for_logistic_regression()
    cont_feature = feature_column.real_valued_column('feature', dimension=4)
    bucketized_feature = feature_column.bucketized_column(
        cont_feature, test_data.get_quantile_based_buckets(iris.data, 10))

