diff --git a/nni/algorithms/hpo/dngo_tuner.py b/nni/algorithms/hpo/dngo_tuner.py
index 09257b0906..276ec75168 100644
--- a/nni/algorithms/hpo/dngo_tuner.py
+++ b/nni/algorithms/hpo/dngo_tuner.py
@@ -40,7 +40,7 @@ def _random_config(search_space, random_state):
     return chosen_config
 
 
-class DngoTuner(Tuner):
+class DNGOTuner(Tuner):
 
     def __init__(self, optimize_mode='maximize', sample_size=1000, trials_per_update=20, num_epochs_per_training=500):
         self.searchspace_json = None
diff --git a/test/ut/sdk/test_builtin_tuners.py b/test/ut/sdk/test_builtin_tuners.py
index 56c318eb21..a60da8ecb6 100644
--- a/test/ut/sdk/test_builtin_tuners.py
+++ b/test/ut/sdk/test_builtin_tuners.py
@@ -12,7 +12,7 @@
 from unittest import TestCase, main
 
 from nni.algorithms.hpo.batch_tuner import BatchTuner
-from nni.algorithms.hpo.dngo_tuner import DngoTuner
+from nni.algorithms.hpo.dngo_tuner import DNGOTuner
 from nni.algorithms.hpo.evolution_tuner import EvolutionTuner
 from nni.algorithms.hpo.gp_tuner import GPTuner
 from nni.algorithms.hpo.gridsearch_tuner import GridSearchTuner
@@ -390,7 +390,7 @@ def test_pbt(self):
         self.import_data_test_for_pbt()
 
     def test_dngo(self):
-        tuner_fn = lambda: DngoTuner(trials_per_update=100, num_epochs_per_training=1)
+        tuner_fn = lambda: DNGOTuner(trials_per_update=100, num_epochs_per_training=1)
         self.search_space_test_all(tuner_fn, fail_types=["choice_str", "choice_mixed",
                                                          "normal", "lognormal", "qnormal", "qlognormal"])
         self.import_data_test(tuner_fn, stype='choice_num')