diff --git a/GPy/testing/serialization_tests.py b/GPy/testing/serialization_tests.py
index f2af89d3..f08148f8 100644
--- a/GPy/testing/serialization_tests.py
+++ b/GPy/testing/serialization_tests.py
@@ -10,7 +10,7 @@ import os
 fixed_seed = 11
 
 
-class Test(unittest.TestCase):
+class TestSerialization:
     def test_serialize_deserialize_kernels(self):
         k1 = GPy.kern.RBF(2, variance=1.0, lengthscale=[1.0, 1.0], ARD=True)
         k2 = GPy.kern.RatQuad(
@@ -371,23 +371,19 @@ class Test(unittest.TestCase):
         m1_r = GPy.models.GPClassification.load_model(
             "temp_test_gp_classifier_with_data.json.zip"
         )
-        self.assertTrue(
-            type(m) == type(m1_r),
-            "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r)),
-        )
+        assert type(m) == type(
+            m1_r
+        ), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r))
         m2_r = GPy.models.GPClassification.load_model(
             "temp_test_gp_classifier_without_data.json.zip", (X, Y)
         )
-        self.assertTrue(
-            type(m) == type(m2_r),
-            "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r)),
-        )
+        assert type(m) == type(m2_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r)),
         os.remove("temp_test_gp_classifier_with_data.json.zip")
         os.remove("temp_test_gp_classifier_without_data.json.zip")
 
         var = m.predict(X)[0]
         var1_r = m1_r.predict(X)[0]
-        var2_r = m2_r.predict(X)[0]
+        _var2_r = m2_r.predict(X)[0]
         np.testing.assert_array_equal(
             np.array(var).flatten(), np.array(var1_r).flatten()
         )
@@ -419,17 +415,11 @@ class Test(unittest.TestCase):
         m1_r = GPy.models.SparseGPClassification.load_model(
             "temp_test_sparse_gp_classifier_with_data.json.zip"
         )
-        self.assertTrue(
-            type(m) == type(m1_r),
-            "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r)),
-        )
+        assert type(m) == type(m1_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r))
         m2_r = GPy.models.SparseGPClassification.load_model(
             "temp_test_sparse_gp_classifier_without_data.json.zip", (X, Y)
         )
-        self.assertTrue(
-            type(m) == type(m2_r),
-            "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r)),
-        )
+        assert type(m) == type(m2_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r)),
         os.remove("temp_test_sparse_gp_classifier_with_data.json.zip")
         os.remove("temp_test_sparse_gp_classifier_without_data.json.zip")
 
@@ -442,8 +432,3 @@ class Test(unittest.TestCase):
         np.testing.assert_array_equal(
             np.array(var).flatten(), np.array(var1_r).flatten()
         )
-
-
-if __name__ == "__main__":
-    # import sys;sys.argv = ['', 'Test.test_parameter_index_operations']
-    unittest.main()