Solved minor bug with MLFlow logger (Lightning-AI#16418)

Resolves Lightning-AI#16411

src/pytorch_lightning/CHANGELOG.md

@@ -132,6 +132,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - 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))
 
+- Fixed an issue with `MLFlowLogger` logging the wrong keys with `.log_hyperparams()` ([#16418](https://github.com/Lightning-AI/lightning/pull/16418))
+
+
 
 ## [1.9.0] - 2023-01-17
 

src/pytorch_lightning/loggers/mlflow.py

@@ -247,7 +247,7 @@ def log_hyperparams(self, params: Union[Dict[str, Any], Namespace]) -> None:
                     f"Mlflow only allows parameters with up to 250 characters. Discard {k}={v}", category=RuntimeWarning
                 )
                 continue
-            params_list.append(Param(key=v, value=v))
+            params_list.append(Param(key=k, value=v))
 
         self.experiment.log_batch(run_id=self.run_id, params=params_list)
 

tests/tests_pytorch/loggers/test_mlflow.py

@@ -253,15 +253,17 @@ def test_mlflow_logger_experiment_calls(client, _, time, param, metric, tmpdir):
     logger.log_hyperparams(params)
 
     logger.experiment.log_batch.assert_called_once_with(
-        run_id=logger.run_id, params=[param(key="test_param", value="test_param")]
+        run_id=logger.run_id, params=[param(key="test", value="test_param")]
     )
+    param.assert_called_with(key="test", value="test_param")
 
     metrics = {"some_metric": 10}
     logger.log_metrics(metrics)
 
     logger.experiment.log_batch.assert_called_with(
         run_id=logger.run_id, metrics=[metric(key="some_metric", value=10, timestamp=1000, step=0)]
     )
+    metric.assert_called_with(key="some_metric", value=10, timestamp=1000, step=0)
 
     logger._mlflow_client.create_experiment.assert_called_once_with(
         name="test", artifact_location="my_artifact_location"