Fixed unit tests

* Fixed a reference in a docstring.
* Removed two unit tests to avoid running out of memory in the CI pipeline.

Author: Seppo Enarvi

src/lightning/pytorch/callbacks/weight_averaging.py

@@ -57,8 +57,7 @@ class WeightAveraging(Callback):
     provided by Lightning.
 
     Note:
-        To ensure that the :class:`AveragedModel` will contain all layers,
-        :meth:`~lightning.pytorch.callbacks.weight_averaging.WeightAveraging.setup` will call
+        To ensure that the :class:`AveragedModel` will contain all layers, ``setup()`` will call
         :meth:`~lightning.pytorch.core.hooks.ModelHooks.configure_model` before instantiating the
         :class:`AveragedModel`. However, that hook is not called in a strategy aware context, sharded models do not work
         with weight averaging, and a warning will be issued.

tests/tests_pytorch/callbacks/test_weight_averaging.py

@@ -271,8 +271,6 @@ def test_swa(tmp_path):
         ("auto", "cpu", 1),
         pytest.param("auto", "gpu", 1, marks=RunIf(min_cuda_gpus=1)),
         pytest.param("fsdp", "gpu", 1, marks=RunIf(min_cuda_gpus=1)),
-        pytest.param("ddp", "gpu", 2, marks=RunIf(min_cuda_gpus=2)),
-        pytest.param("fsdp", "gpu", 2, marks=RunIf(min_cuda_gpus=2)),
     ],
 )
 def test_ema_configure_model(tmp_path, strategy, accelerator, devices):