Fix save_hyperparameters for multiple inheritance and mixins

src/pytorch_lightning/CHANGELOG.md

@@ -29,7 +29,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Fixed
 
--
+- Fixed an unintended limitation for calling `save_hyperparameters` on mixin classes that don't subclass `LightningModule`/`LightningDataModule` ([#16369](https://github.com/Lightning-AI/lightning/pull/16369))
 
 
 ## [1.9.0] - 2023-01-17

src/pytorch_lightning/utilities/parsing.py

@@ -137,10 +137,10 @@ def _get_first_if_any(
     return n_self, n_args, n_kwargs
 
 
-def get_init_args(frame: types.FrameType) -> Dict[str, Any]:
+def get_init_args(frame: types.FrameType) -> Tuple[Optional[Any], Dict[str, Any]]:
     _, _, _, local_vars = inspect.getargvalues(frame)
     if "__class__" not in local_vars:
-        return {}
+        return None, {}
     cls = local_vars["__class__"]
     init_parameters = inspect.signature(cls.__init__).parameters
     self_var, args_var, kwargs_var = parse_class_init_keys(cls)
@@ -152,7 +152,8 @@ def get_init_args(frame: types.FrameType) -> Dict[str, Any]:
     if kwargs_var:
         local_args.update(local_args.get(kwargs_var, {}))
     local_args = {k: v for k, v in local_args.items() if k not in exclude_argnames}
-    return local_args
+    self_arg = local_vars.get(self_var, None)
+    return self_arg, local_args
 
 
 def collect_init_args(
@@ -179,8 +180,8 @@ def collect_init_args(
     if not isinstance(frame.f_back, types.FrameType):
         return path_args
 
-    if "__class__" in local_vars and (not classes or issubclass(local_vars["__class__"], classes)):
-        local_args = get_init_args(frame)
+    local_self, local_args = get_init_args(frame)
+    if "__class__" in local_vars and (not classes or isinstance(local_self, classes)):
         # recursive update
         path_args.append(local_args)
         return collect_init_args(frame.f_back, path_args, inside=True, classes=classes)

tests/tests_pytorch/models/test_hparams.py

@@ -296,6 +296,24 @@ def __init__(self, *args, subclass_arg=1200, **kwargs):
         self.save_hyperparameters()
 
 
+class MixinForBoringModel:
+    any_other_loss = torch.nn.CrossEntropyLoss()
+
+    def __init__(self, *args, subclass_arg=1200, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.save_hyperparameters()
+
+
+class BoringModelWithMixin(MixinForBoringModel, CustomBoringModel):
+    pass
+
+
+class BoringModelWithMixinAndInit(MixinForBoringModel, CustomBoringModel):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.save_hyperparameters()
+
+
 class NonSavingSubClassBoringModel(CustomBoringModel):
     any_other_loss = torch.nn.CrossEntropyLoss()
 
@@ -345,6 +363,8 @@ class DictConfSubClassBoringModel:
         AggSubClassBoringModel,
         UnconventionalArgsBoringModel,
         pytest.param(DictConfSubClassBoringModel, marks=RunIf(omegaconf=True)),
+        BoringModelWithMixin,
+        BoringModelWithMixinAndInit,
     ],
 )
 def test_collect_init_arguments(tmpdir, cls):
@@ -360,7 +380,7 @@ def test_collect_init_arguments(tmpdir, cls):
     model = cls(batch_size=179, **extra_args)
     assert model.hparams.batch_size == 179
 
-    if isinstance(model, (SubClassBoringModel, NonSavingSubClassBoringModel)):
+    if isinstance(model, (SubClassBoringModel, NonSavingSubClassBoringModel, MixinForBoringModel)):
         assert model.hparams.subclass_arg == 1200
 
     if isinstance(model, AggSubClassBoringModel):

tests/tests_pytorch/utilities/test_parsing.py

@@ -255,10 +255,10 @@ def get_init_args_wrapper(self):
             self.result = get_init_args(frame)
 
     my_class = AutomaticArgsModel("test", anykw=32, otherkw=123)
-    assert my_class.result == {"anyarg": "test", "anykw": 32, "otherkw": 123}
+    assert my_class.result == (my_class, {"anyarg": "test", "anykw": 32, "otherkw": 123})
 
     my_class.get_init_args_wrapper()
-    assert my_class.result == {}
+    assert my_class.result == (None, {})
 
 
 def test_collect_init_args():