Test coverage for unconditional MVNScore.sample

Author: han-ol

tests/test_scores/test_scores.py

@@ -46,3 +46,17 @@ def test_mean_score_optimality(mean_score, random_conditions):
 
     assert suboptimal_score > optimal_score
     assert keras.ops.isclose(optimal_score, 0)
+
+
+def test_unconditional_mvn(multivariate_normal_score):
+    mean = keras.ops.convert_to_tensor([[0.0, 1.0]])
+    covariance = keras.ops.convert_to_tensor([[[1.0, 0.0], [0.0, 1.0]]])
+    multivariate_normal_score.sample((10,), mean, covariance)
+
+
+def test_unconditional_mvn_value_error(multivariate_normal_score):
+    mean = keras.ops.convert_to_tensor([0.0, 1.0])
+    covariance = keras.ops.convert_to_tensor([[1.0, 0.0], [0.0, 1.0]])
+
+    with pytest.raises(ValueError):
+        multivariate_normal_score.sample((10,), mean, covariance)