Add test

src/sparseml/core/session.py

@@ -271,8 +271,7 @@ def event(
         if loss is not None:
             self.state.loss = loss
 
-        self._log_model_info(event_type=event_type)
-        self._log_loss(event_type=event_type, loss=loss)
+        self.log(event_type=event_type, loss=loss)
 
         return ModifiedState(
             model=self.state.model.model if self.state.model else None,
@@ -281,6 +280,16 @@ def event(
             modifier_data=mod_data,
         )
 
+    def log(self, event_type: EventType, loss: Optional[Any] = None):
+        """
+        Log model and loss information for the current event type
+
+        :param event_type: the event type to log for
+        :param loss: the loss to log if any
+        """
+        self._log_model_info()
+        self._log_loss(event_type=event_type, loss=loss)
+
     def reset(self):
         """
         Reset the session to its initial state
@@ -301,8 +310,8 @@ def get_serialized_recipe(self) -> str:
         recipe = self.lifecycle.recipe_container.compiled_recipe
         return recipe.yaml()
 
-    def _log_model_info(self, event_type: EventType):
-        # Log model level logs if needed
+    def _log_model_info(self):
+        # Log model level logs if cadence reached
 
         epoch = self._lifecycle.event_lifecycle.current_index
 

tests/sparseml/core/test_session.py

@@ -167,6 +167,24 @@ def test_apply_calls_lifecycle_initialize_and_finalize(
             lifecycle_mock._hit_count["finalize"] == 1
         ), "apply did not invoke the lifecycle finalize method"
 
+    def test_log_methods_called_same_number_of_times(
+        self, mocker, monkeypatch, setup_active_session
+    ):
+        mock_log_model_info = mocker.patch.object(
+            setup_active_session, "_log_model_info"
+        )
+        mock_log_loss = mocker.patch.object(setup_active_session, "_log_loss")
+        monkeypatch.setattr(setup_active_session, "_lifecycle", LifeCycleMock())
+
+        event_type = EventType.BATCH_START
+        batch_data = None
+        loss = None
+
+        setup_active_session.initialize(framework=Framework.pytorch)
+        setup_active_session.event(event_type, batch_data, loss)
+
+        assert mock_log_model_info.call_count == mock_log_loss.call_count
+
 
 @pytest.mark.parametrize(
     "attribute_name",