diff --git a/src/nemos/glm.py b/src/nemos/glm.py
index c4de380c..c38c2216 100644
--- a/src/nemos/glm.py
+++ b/src/nemos/glm.py
@@ -1017,6 +1017,7 @@ def update(
         return opt_step
 
     def get_optimal_solver_params_config(self):
+        """Return the functions for computing default step and batch size for the solver."""
         return glm_compute_optimal_stepsize_configs(self)
 
 
diff --git a/tests/conftest.py b/tests/conftest.py
index 8a36fadf..a235f7b3 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -82,6 +82,9 @@ def initialize_params(self, *args, **kwargs):
     def _predict_and_compute_loss(self, params, X, y):
         pass
 
+    def get_optimal_solver_params_config(self):
+        return None, None, None
+
 
 class MockRegressorNested(MockRegressor):
     def __init__(self, other_param: int, std_param: int = 0):
diff --git a/tests/test_base_class.py b/tests/test_base_class.py
index 4af81c30..1f89f7d6 100644
--- a/tests/test_base_class.py
+++ b/tests/test_base_class.py
@@ -24,6 +24,8 @@ def predict(self, X: Union[NDArray, jnp.ndarray]) -> jnp.ndarray:
     def score(self, X, y, score_type="pseudo-r2-McFadden"):
         pass
 
+    def get_optimal_solver_params_config(self):
+        return None, None, None
 
 class BadEstimator(Base):
     def __init__(self, param1, *args):