Resolve model metadata for saved models that do not define an artifac…

…t_path (mlflow#11166)

Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>

mlflow/models/model.py

@@ -285,10 +285,8 @@ def __init__(
         **kwargs,
     ):
         # store model id instead of run_id and path to avoid confusion when model gets exported
-        if run_id:
-            self.run_id = run_id
-            self.artifact_path = artifact_path
-
+        self.run_id = run_id
+        self.artifact_path = artifact_path
         self.utc_time_created = str(utc_time_created or datetime.utcnow())
         self.flavors = flavors if flavors is not None else {}
         self.signature = signature

tests/models/test_model.py

@@ -479,3 +479,10 @@ def predict(self, context, model_input, params=None):
     assert loaded_model.saved_input_example_info["type"] == "json_object"
     loaded_example = loaded_model.load_input_example(local_path)
     assert loaded_example == input_example
+
+
+def test_model_saved_by_save_model_can_be_loaded(tmp_path, sklearn_knn_model):
+    mlflow.sklearn.save_model(sklearn_knn_model, tmp_path)
+    info = Model.load(tmp_path).get_model_info()
+    assert info.run_id is None
+    assert info.artifact_path is None