docs

autofit/mapper/model.py

@@ -423,8 +423,24 @@ def __len__(self):
         return len(self.values())
 
     def as_model(
-        self, model_classes=tuple(), excluded_classes=tuple(),
+        self,
+        model_classes: Union[type, Iterable[type]] = tuple(),
+        excluded_classes: Union[type, Iterable[type]] = tuple(),
     ):
+        """
+        Convert this instance to a model
+
+        Parameters
+        ----------
+        model_classes
+            The classes to convert to models
+        excluded_classes
+            The classes to exclude from conversion
+
+        Returns
+        -------
+        A model
+        """
 
         from autofit.mapper.prior_model.abstract import AbstractPriorModel
 

autofit/mapper/prior_model/abstract.py

@@ -1007,14 +1007,19 @@ def random_instance(self, ignore_prior_limits=False):
     @staticmethod
     @DynamicRecursionCache()
     def from_instance(
-        instance, model_classes=tuple(), exclude_classes=tuple(),
+        instance,
+        model_classes: Union[type, Iterable[type]] = tuple(),
+        exclude_classes: Union[type, Iterable[type]] = tuple(),
     ):
         """
         Recursively create a prior object model from an object model.
 
         Parameters
         ----------
         model_classes
+            A tuple of classes that should be converted to a prior model
+        exclude_classes
+            A tuple of classes that should not be converted to a prior model
         instance
             A dictionary, list, class instance or model instance
         Returns