Improved parameter validation for TorchForecastingModel

CHANGELOG.md

@@ -21,6 +21,8 @@ but cannot always guarantee backwards compatibility. Changes that may **break co
 ### For developers of the library:
 
 - Fixed all warnings when generating the documentation. Also, the documentation can now be generated without having to re-install Darts before every run. [#2936](https://github.com/unit8co/darts/pull/2936) by [Dennis Bader](https://github.com/dennisbader).
+ - Reworked the `_validate_model_params` function of `TorchForecastingModel` to support more complicated cases of class inheritance. [#2908](https://github.com/unit8co/darts/pull/2908) by [Tim Rosenflanz](https://github.com/trosenflanz).
+
 
 ## [0.38.0](https://github.com/unit8co/darts/tree/0.38.0) (2025-10-03)
 

darts/models/forecasting/torch_forecasting_model.py

@@ -363,14 +363,22 @@ def encode_year(idx):
 
     @classmethod
     def _validate_model_params(cls, **kwargs):
-        """validate that parameters used at model creation are part of :class:`TorchForecastingModel`,
-        :class:`PLForecastingModule` or cls __init__ methods.
+        """validate that parameters used at model creation are part of the model cls __init__,
+        its parents __init__ methods, or :class:`PLForecastingModule`
         """
-        valid_kwargs = (
-            set(inspect.signature(TorchForecastingModel.__init__).parameters.keys())
-            | set(inspect.signature(PLForecastingModule.__init__).parameters.keys())
-            | set(inspect.signature(cls.__init__).parameters.keys())
+        # initiate with PLForecastingModule params that isn't part of the base class
+        valid_kwargs = set(
+            inspect.signature(PLForecastingModule.__init__).parameters.keys()
         )
+        # add params from the full list of base classes
+        for base in inspect.getmro(cls):
+            if base is object:
+                break
+            sig = inspect.signature(base.__init__)
+            valid_kwargs.update(sig.parameters.keys())
+        # Remove 'self','args,'kwargs' from consideration
+        for generic_arg in ["self", "args", "kwargs"]:
+            valid_kwargs.discard(generic_arg)
 
         invalid_kwargs = [kwarg for kwarg in kwargs if kwarg not in valid_kwargs]
 

darts/tests/models/forecasting/test_torch_forecasting_model.py

@@ -1488,6 +1488,26 @@ def test_wrong_model_creation_params(self):
         with pytest.raises(ValueError):
             _ = RNNModel(12, "RNN", 10, 10, **invalid_kwarg)
 
+    def test_inherited_wrong_model_creation_params(self):
+        # test using inheritance class
+        class RnnModelLambda(RNNModel):
+            def __init__(self, positional_param, named_param=0, *args, **kwargs):
+                super().__init__(*args, **kwargs)
+
+        valid_kwargs = {
+            "pl_trainer_kwargs": {},
+            "named_param": 1,
+            "positional_param": 1,
+        }
+        invalid_kwargs = {"some_invalid_kwarg": None}
+
+        # valid params should not raise an error
+        _ = RnnModelLambda(0, input_chunk_length=12, **valid_kwargs)
+
+        # invalid params should raise an error
+        with pytest.raises(ValueError):
+            _ = RnnModelLambda(0, input_chunk_length=12, **invalid_kwargs)
+
     def test_metrics(self):
         metric = MeanAbsolutePercentageError()
         metric_collection = MetricCollection([