Add run_name argument to the MLFlowLogger constructor

CHANGELOG.md

@@ -61,6 +61,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - MLflowLogger now uses the env variable `MLFLOW_TRACKING_URI` as default tracking uri ([#7457](https://github.com/PyTorchLightning/pytorch-lightning/pull/7457))
 
 
+- MLFlowLogger now accepts `run_name` as an constructor argument ([#7622](https://github.com/PyTorchLightning/pytorch-lightning/issues/7622))
+
+
 ### Deprecated
 
 

pytorch_lightning/loggers/mlflow.py

@@ -31,10 +31,12 @@
 try:
     import mlflow
     from mlflow.tracking import context, MlflowClient
+    from mlflow.utils.mlflow_tags import MLFLOW_RUN_NAME
 # todo: there seems to be still some remaining import error with Conda env
 except ImportError:
     _MLFLOW_AVAILABLE = False
     mlflow, MlflowClient, context = None, None, None
+    MLFLOW_RUN_NAME = "mlflow.runName"
 
 # before v1.1.0
 if hasattr(context, 'resolve_tags'):
@@ -85,6 +87,8 @@ def any_lightning_module_function_or_hook(self):
 
     Args:
         experiment_name: The name of the experiment
+        run_name: Name of the new run. The `run_name` is internally stored as a ``mlflow.runName`` tag.
+            If the ``mlflow.runName`` tag has already been set in `tags`, the value is overridden by the `run_name`.
         tracking_uri: Address of local or remote tracking server.
             If not provided, defaults to `MLFLOW_TRACKING_URI` environment variable if set, otherwise it falls
             back to `file:<save_dir>`.
@@ -106,6 +110,7 @@ def any_lightning_module_function_or_hook(self):
     def __init__(
         self,
         experiment_name: str = 'default',
+        run_name: Optional[str] = None,
         tracking_uri: Optional[str] = os.getenv('MLFLOW_TRACKING_URI'),
         tags: Optional[Dict[str, Any]] = None,
         save_dir: Optional[str] = './mlruns',
@@ -124,6 +129,7 @@ def __init__(
         self._experiment_name = experiment_name
         self._experiment_id = None
         self._tracking_uri = tracking_uri
+        self._run_name = run_name
         self._run_id = None
         self.tags = tags
         self._prefix = prefix
@@ -155,6 +161,14 @@ def experiment(self) -> MlflowClient:
                 )
 
         if self._run_id is None:
+            if self._run_name is not None:
+                self.tags = self.tags or {}
+                if MLFLOW_RUN_NAME in self.tags:
+                    log.warning(
+                        f'The tag {MLFLOW_RUN_NAME} is found in tags. '
+                        f'The value will be overridden by {self._run_name}.'
+                    )
+                self.tags[MLFLOW_RUN_NAME] = self._run_name
             run = self._mlflow_client.create_run(experiment_id=self._experiment_id, tags=resolve_tags(self.tags))
             self._run_id = run.info.run_id
         return self._mlflow_client

tests/loggers/test_mlflow.py

@@ -19,6 +19,7 @@
 
 from pytorch_lightning import Trainer
 from pytorch_lightning.loggers import _MLFLOW_AVAILABLE, MLFlowLogger
+from pytorch_lightning.loggers.mlflow import MLFLOW_RUN_NAME, resolve_tags
 from tests.helpers import BoringModel
 
 
@@ -85,6 +86,33 @@ def test_mlflow_logger_exists(client, mlflow, tmpdir):
     assert logger3.run_id == "run-id-3"
 
 
+@mock.patch('pytorch_lightning.loggers.mlflow.mlflow')
+@mock.patch('pytorch_lightning.loggers.mlflow.MlflowClient')
+def test_mlflow_run_name_setting(client, mlflow, tmpdir):
+    """ Test that the run_name argument makes the MLFLOW_RUN_NAME tag. """
+
+    tags = resolve_tags({MLFLOW_RUN_NAME: 'run-name-1'})
+
+    # run_name is appended to tags
+    logger = MLFlowLogger('test', run_name='run-name-1', save_dir=tmpdir)
+    logger = mock_mlflow_run_creation(logger, experiment_id='exp-id')
+    _ = logger.experiment
+    client.return_value.create_run.assert_called_with(experiment_id='exp-id', tags=tags)
+
+    # run_name overrides tags[MLFLOW_RUN_NAME]
+    logger = MLFlowLogger('test', run_name='run-name-1', tags={MLFLOW_RUN_NAME: "run-name-2"}, save_dir=tmpdir)
+    logger = mock_mlflow_run_creation(logger, experiment_id='exp-id')
+    _ = logger.experiment
+    client.return_value.create_run.assert_called_with(experiment_id='exp-id', tags=tags)
+
+    # default run_name (= None) does not append new tag
+    logger = MLFlowLogger('test', save_dir=tmpdir)
+    logger = mock_mlflow_run_creation(logger, experiment_id='exp-id')
+    _ = logger.experiment
+    default_tags = resolve_tags(None)
+    client.return_value.create_run.assert_called_with(experiment_id='exp-id', tags=default_tags)
+
+
 @mock.patch("pytorch_lightning.loggers.mlflow.mlflow")
 @mock.patch("pytorch_lightning.loggers.mlflow.MlflowClient")
 def test_mlflow_log_dir(client, mlflow, tmpdir):