Try to fix experiment already exist issue in MLFlowHandler

monai/handlers/mlflow_handler.py

@@ -21,6 +21,7 @@
 import torch
 from torch.utils.data import Dataset
 
+from monai.apps.utils import get_logger
 from monai.config import IgniteInfo
 from monai.utils import CommonKeys, ensure_tuple, min_version, optional_import
 
@@ -29,6 +30,9 @@
 mlflow.entities, _ = optional_import(
     "mlflow.entities", descriptor="Please install mlflow.entities before using MLFlowHandler."
 )
+MlflowException, _ = optional_import(
+    "mlflow.exceptions", name="MlflowException", descriptor="Please install mlflow before using MLFlowHandler."
+)
 pandas, _ = optional_import("pandas", descriptor="Please install pandas for recording the dataset.")
 tqdm, _ = optional_import("tqdm", "4.47.0", min_version, "tqdm")
 
@@ -41,6 +45,8 @@
 
 DEFAULT_TAG = "Loss"
 
+logger = get_logger(module_name=__name__)
+
 
 class MLFlowHandler:
     """
@@ -236,10 +242,21 @@ def start(self, engine: Engine) -> None:
     def _set_experiment(self):
         experiment = self.experiment
         if not experiment:
-            experiment = self.client.get_experiment_by_name(self.experiment_name)
-            if not experiment:
-                experiment_id = self.client.create_experiment(self.experiment_name)
-                experiment = self.client.get_experiment(experiment_id)
+            for _retry_time in range(3):
+                try:
+                    experiment = self.client.get_experiment_by_name(self.experiment_name)
+                    if not experiment:
+                        experiment_id = self.client.create_experiment(self.experiment_name)
+                        experiment = self.client.get_experiment(experiment_id)
+                    break
+                except MlflowException as e:
+                    if "RESOURCE_ALREADY_EXISTS" in str(e):
+                        logger.warning("Experiment already exists; delaying before retrying.")
+                        time.sleep(1)
+                        if _retry_time == 2:
+                            raise e
+                    else:
+                        raise e
 
         if experiment.lifecycle_stage != mlflow.entities.LifecycleStage.ACTIVE:
             raise ValueError(f"Cannot set a deleted experiment '{self.experiment_name}' as the active experiment")