Make the system metrics tests independent of the installed mlflow

The monitor is only started when the mlflow system metrics module is
importable, so the tests that assert it starts were relying on that
being true in the environment they run in. Pin it for those tests and
cover the case where it is missing, where the workflow should carry on
with a warning.

Signed-off-by: uditmahato <uditmahato29271@gmail.com>

Author: uditmahato

tests/handlers/test_handler_mlflow.py

@@ -270,7 +270,10 @@ def _train_func(engine, batch):
                 close_on_complete=True,
             )
             monitor = MagicMock()
-            with patch("monai.handlers.mlflow_handler.SystemMetricsMonitor", return_value=monitor) as monitor_class:
+            with (
+                patch("monai.handlers.mlflow_handler.SystemMetricsMonitor", return_value=monitor) as monitor_class,
+                patch("monai.handlers.mlflow_handler.has_system_metrics", True),
+            ):
                 handler.attach(engine)
                 engine.run(range(3), max_epochs=1)
 
@@ -303,7 +306,10 @@ def _train_func(engine, batch):
                 for _ in range(3)
             ]
             monitor = MagicMock()
-            with patch("monai.handlers.mlflow_handler.SystemMetricsMonitor", return_value=monitor) as monitor_class:
+            with (
+                patch("monai.handlers.mlflow_handler.SystemMetricsMonitor", return_value=monitor) as monitor_class,
+                patch("monai.handlers.mlflow_handler.has_system_metrics", True),
+            ):
                 for handler in handlers:
                     handler.start(engine)
 
@@ -322,6 +328,31 @@ def _train_func(engine, batch):
             for handler in handlers:
                 handler.close()
 
+    def test_system_metrics_warns_when_mlflow_is_too_old(self):
+        """
+        Test that a workflow still runs, with a warning, when the installed mlflow cannot
+        record the system metrics.
+        """
+        with tempfile.TemporaryDirectory() as tempdir:
+
+            def _train_func(engine, batch):
+                return [batch + 1.0]
+
+            engine = Engine(_train_func)
+            test_path = os.path.join(tempdir, "mlflow_system_metrics_unavailable")
+            handler = MLFlowHandler(
+                iteration_log=False,
+                tracking_uri=path_to_uri(test_path),
+                log_system_metrics=True,
+                close_on_complete=True,
+            )
+            with patch("monai.handlers.mlflow_handler.has_system_metrics", False):
+                with self.assertWarns(Warning):
+                    handler.attach(engine)
+                    engine.run(range(3), max_epochs=1)
+
+            self.assertIsNone(handler.system_metrics_monitor)
+
     def test_system_metrics_settings_are_validated(self):
         """
         Test that a sampling setting that mlflow does not define a behaviour for is rejected.