[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

tests/tests_pytorch/loggers/test_mlflow.py

@@ -428,31 +428,46 @@ def test_set_tracking_uri(mlflow_mock):
     _ = logger.experiment
     mlflow_mock.set_tracking_uri.assert_called_with("the_tracking_uri")
 
+
 def test_mlflowlogger_metric_deduplication(monkeypatch):
     import types
+
     from lightning.pytorch.loggers.mlflow import MLFlowLogger
 
     # Dummy MLflow client to record log_batch calls
     logged_metrics = []
+
     class DummyMlflowClient:
         def log_batch(self, run_id, metrics, **kwargs):
             logged_metrics.extend(metrics)
-        def set_tracking_uri(self, uri): pass
-        def create_run(self, experiment_id, tags): 
-            class Run: info = types.SimpleNamespace(run_id="dummy_run_id")
+
+        def set_tracking_uri(self, uri):
+            pass
+
+        def create_run(self, experiment_id, tags):
+            class Run:
+                info = types.SimpleNamespace(run_id="dummy_run_id")
+
             return Run()
+
         def get_run(self, run_id):
-            class Run: info = types.SimpleNamespace(experiment_id="dummy_experiment_id")
+            class Run:
+                info = types.SimpleNamespace(experiment_id="dummy_experiment_id")
+
             return Run()
-        def get_experiment_by_name(self, name): return None
-        def create_experiment(self, name, artifact_location=None): return "dummy_experiment_id"
+
+        def get_experiment_by_name(self, name):
+            return None
+
+        def create_experiment(self, name, artifact_location=None):
+            return "dummy_experiment_id"
 
     # Patch the MLFlowLogger to use DummyMlflowClient
     monkeypatch.setattr("mlflow.tracking.MlflowClient", lambda *a, **k: DummyMlflowClient())
 
     logger = MLFlowLogger(experiment_name="test_exp")
-    logger.log_metrics({'foo': 1.0}, step=5)
-    logger.log_metrics({'foo': 1.0}, step=5)  # duplicate
+    logger.log_metrics({"foo": 1.0}, step=5)
+    logger.log_metrics({"foo": 1.0}, step=5)  # duplicate
 
     # Only the first metric should be logged
     assert len(logged_metrics) == 1