Fix SpikeDetection.load_state_dict referencing nonexistent self.running

`SpikeDetection.__init__` stores the running-mean metric on
`self.running_mean` (line 57). `SpikeDetection.state_dict` saves it under
the key `"running"` via `self.running_mean.state_dict()` (line 156).
`SpikeDetection.load_state_dict` then tries to restore it with
`self.running.load_state_dict(...)` — but `self.running` is never defined,
so any resume of a SpikeDetection callback state crashes with:

    AttributeError: 'SpikeDetection' object has no attribute 'running'

The asymmetry with the symmetric line right below it
(`self.running_mean.base_metric.load_state_dict(...)`) confirms it's a
typo of `self.running_mean`, not a deliberate different attribute. Adds a
regression test that round-trips state_dict / load_state_dict on a fresh
SpikeDetection.

Author: Kymi808

src/lightning/fabric/utilities/spike.py

@@ -165,7 +165,7 @@ def load_state_dict(self, state_dict: dict[str, Any]) -> None:
         self.rtol = state_dict.pop("rtol")
         self.bad_batches = state_dict.pop("bad_batches")
         self.exclude_batches_path = state_dict.pop("bad_batches_path")
-        self.running.load_state_dict(state_dict.pop("running"))
+        self.running_mean.load_state_dict(state_dict.pop("running"))
         self.running_mean.base_metric.load_state_dict(state_dict.pop("mean"))
 
 

tests/tests_fabric/utilities/test_spike.py

@@ -81,3 +81,15 @@ def test_fabric_spike_detection_integration(tmp_path, global_rank_spike, num_dev
         spike_value=spike_value,
         should_raise=should_raise,
     )
+
+
+@pytest.mark.skipif(not _TORCHMETRICS_GREATER_EQUAL_1_0_0, reason="requires torchmetrics>=1.0.0")
+def test_spike_detection_state_dict_roundtrip():
+    # Regression: ``load_state_dict`` previously called
+    # ``self.running.load_state_dict(...)`` but the attribute is named
+    # ``self.running_mean`` (set in ``__init__``), so any resume of a
+    # SpikeDetection callback crashed with
+    # ``AttributeError: 'SpikeDetection' object has no attribute 'running'``.
+    src = SpikeDetection()
+    dst = SpikeDetection()
+    dst.load_state_dict(src.state_dict())