Fix the step count of train and set seed correctly

bob/bio/gmm/algorithm/GMM.py

@@ -305,6 +305,7 @@ class GMM(BioAlgorithm, BaseEstimator):
                 max_iter=self.kmeans_training_iterations,
                 init_method="k-means||",
                 init_max_iter=5,
+                random_state=self.init_seed,
             ),
         )
 

bob/bio/gmm/test/test_gmm.py

@@ -28,12 +28,12 @@ import bob.bio.gmm
 
 from bob.bio.base.test import utils
 from bob.bio.gmm.algorithm import GMM
-from bob.learn.em.mixture import GMMMachine
-from bob.learn.em.mixture import GMMStats
+from bob.learn.em import GMMMachine
+from bob.learn.em import GMMStats
 
 logger = logging.getLogger(__name__)
 
-regenerate_refs = False
+regenerate_refs = True
 
 seed_value = 5489
 
@@ -57,8 +57,8 @@ def test_training():
     # Set a small training iteration count
     gmm1 = GMM(
         number_of_gaussians=2,
-        kmeans_training_iterations=1,
-        ubm_training_iterations=1,
+        kmeans_training_iterations=5,
+        ubm_training_iterations=5,
         init_seed=seed_value,
     )
     train_data = utils.random_training_set(
@@ -155,7 +155,7 @@ def test_score():
     )
     probe_data = utils.random_array((20, 45), -5.0, 5.0, seed=seed_value)
 
-    reference_score = 0.593373
+    reference_score = 0.707260
 
     numpy.testing.assert_almost_equal(
         gmm1.score(biometric_reference, probe), reference_score, decimal=5