from tensorflow.contrib.learn.python.learn.estimators import estimator_test_utils

    'loss',
    'precision/positive_threshold_0.500000_mean',
    'recall/positive_threshold_0.500000_mean',
}


class DNNLinearCombinedClassifierBenchmark(test.Benchmark):

  def _assertSingleClassMetrics(self, metrics):
    estimator_test_utils.assert_in_range(0.9, 1.0, 'auc', metrics)
    estimator_test_utils.assert_in_range(0.9, 1.0,
                                         'accuracy/threshold_0.500000_mean',
                                         metrics)
    estimator_test_utils.assert_in_range(
        0.9, 1.0, 'precision/positive_threshold_0.500000_mean', metrics)
    estimator_test_utils.assert_in_range(
        0.9, 1.0, 'recall/positive_threshold_0.500000_mean', metrics)
    self._assertCommonMetrics(metrics)

  def _assertCommonMetrics(self, metrics):
    estimator_test_utils.assert_in_range(_ITERS, _ITERS + 5, 'global_step',
                                         metrics)
    estimator_test_utils.assert_in_range(0.9, 1.0, 'accuracy', metrics)
    estimator_test_utils.assert_in_range(0.0, 0.2, 'loss', metrics)
    self.report_benchmark(
        iters=metrics['global_step'],
