Fix `save_hyperparameters` when no parameters need saving (#11827)

CHANGELOG.md

@@ -610,6 +610,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Configure native Deepspeed schedulers with interval='step' ([#11788](https://github.com/PyTorchLightning/pytorch-lightning/pull/11788))
 
 
+- Fixed an `AttributeError` when calling `save_hyperparameters` and no parameters need saving ([#11827](https://github.com/PyTorchLightning/pytorch-lightning/pull/11827))
+
+
 ## [1.5.9] - 2022-01-20
 
 ### Fixed

pytorch_lightning/utilities/parsing.py

@@ -224,7 +224,6 @@ def save_hyperparameters(
         init_args = {}
         for local_args in collect_init_args(frame, []):
             init_args.update(local_args)
-    assert init_args, "failed to inspect the obj init"
 
     if ignore is not None:
         if isinstance(ignore, str):
@@ -249,8 +248,7 @@ def save_hyperparameters(
             obj._hparams_name = "kwargs"
 
     # `hparams` are expected here
-    if hp:
-        obj._set_hparams(hp)
+    obj._set_hparams(hp)
     # make deep copy so  there is not other runtime changes reflected
     obj._hparams_initial = copy.deepcopy(obj._hparams)
 

tests/models/test_hparams.py

@@ -672,6 +672,31 @@ def test_ignore_args_list_hparams(tmpdir, ignore):
         assert arg not in model.hparams
 
 
+class IgnoreAllParametersModel(BoringModel):
+    def __init__(self, arg1, arg2, arg3):
+        super().__init__()
+        self.save_hyperparameters(ignore=("arg1", "arg2", "arg3"))
+
+
+class NoParametersModel(BoringModel):
+    def __init__(self):
+        super().__init__()
+        self.save_hyperparameters()
+
+
+@pytest.mark.parametrize(
+    "model",
+    (
+        IgnoreAllParametersModel(arg1=14, arg2=90, arg3=50),
+        NoParametersModel(),
+    ),
+)
+def test_save_no_parameters(model):
+    """Test that calling save_hyperparameters works if no parameters need saving."""
+    assert model.hparams == {}
+    assert model._hparams_initial == {}
+
+
 class HparamsKwargsContainerModel(BoringModel):
     def __init__(self, **kwargs):
         super().__init__()