Add multi-thread unittest for mlflow handler

tests/test_handler_mlflow.py

@@ -11,8 +11,10 @@
 
 import glob
 import os
+import shutil
 import tempfile
 import unittest
+from concurrent.futures import ThreadPoolExecutor
 
 import numpy as np
 from ignite.engine import Engine, Events
@@ -21,7 +23,38 @@
 from monai.utils import path_to_uri
 
 
+def dummy_train(tracking_folder):
+    tempdir = tempfile.mkdtemp()
+
+    # set up engine
+    def _train_func(engine, batch):
+        return [batch + 1.0]
+
+    engine = Engine(_train_func)
+
+    # set up testing handler
+    test_path = os.path.join(tempdir, tracking_folder)
+    handler = MLFlowHandler(
+        iteration_log=False,
+        epoch_log=True,
+        tracking_uri=path_to_uri(test_path),
+        state_attributes=["test"],
+        close_on_complete=True,
+    )
+    handler.attach(engine)
+    engine.run(range(3), max_epochs=2)
+    return test_path
+
+
 class TestHandlerMLFlow(unittest.TestCase):
+    def setUp(self):
+        self.tmpdir_list = []
+
+    def tearDown(self):
+        for tmpdir in self.tmpdir_list:
+            if tmpdir and os.path.exists(tmpdir):
+                shutil.rmtree(tmpdir)
+
     def test_metrics_track(self):
         experiment_param = {"backbone": "efficientnet_b0"}
         with tempfile.TemporaryDirectory() as tempdir:
@@ -61,6 +94,18 @@ def _update_metric(engine):
             # check logging output
             self.assertTrue(len(glob.glob(test_path)) > 0)
 
+    def test_multi_thread(self):
+        test_uri_list = ["monai_mlflow_test1", "monai_mlflow_test2"]
+        with ThreadPoolExecutor(2, "Training") as executor:
+            futures = {}
+            for t in test_uri_list:
+                futures[t] = executor.submit(dummy_train, t)
+
+            for _, future in futures.items():
+                res = future.result()
+                self.tmpdir_list.append(res)
+                self.assertTrue(len(glob.glob(res)) > 0)
+
 
 if __name__ == "__main__":
     unittest.main()