activate tests for multivariate normal score

Author: vpratz

tests/test_approximators/test_fit.py

@@ -3,7 +3,6 @@
 import pytest
 import io
 from contextlib import redirect_stdout
-from tests.utils import check_approximator_multivariate_normal_score
 
 
 @pytest.mark.skip(reason="not implemented")
@@ -20,9 +19,6 @@ def test_fit(amortizer, dataset):
 
 
 def test_loss_progress(approximator, train_dataset, validation_dataset):
-    # as long as MultivariateNormalScore is unstable, skip fit progress test
-    check_approximator_multivariate_normal_score(approximator)
-
     approximator.compile(optimizer="AdamW")
     num_epochs = 3
 

tests/test_approximators/test_point_approximators/test_sample.py

@@ -1,15 +1,12 @@
 import keras
 import numpy as np
 from bayesflow.scores import ParametricDistributionScore
-from tests.utils import check_combination_simulator_adapter, check_approximator_multivariate_normal_score
+from tests.utils import check_combination_simulator_adapter
 
 
 def test_approximator_sample(point_approximator, simulator, batch_size, num_samples, adapter):
     check_combination_simulator_adapter(simulator, adapter)
 
-    # as long as MultivariateNormalScore is unstable, skip test
-    check_approximator_multivariate_normal_score(point_approximator)
-
     data = simulator.sample((batch_size,))
 
     batch = adapter(data)