[tune] check for running session (#10840)

python/ray/tune/__init__.py

@@ -9,9 +9,9 @@ from ray.tune.registry import register_env, register_trainable
 from ray.tune.trainable import Trainable
 from ray.tune.durable_trainable import DurableTrainable
 from ray.tune.suggest import grid_search
-from ray.tune.session import (report, get_trial_dir, get_trial_name,
-                              get_trial_id, make_checkpoint_dir,
-                              save_checkpoint, checkpoint_dir)
+from ray.tune.session import (
+    report, get_trial_dir, get_trial_name, get_trial_id, make_checkpoint_dir,
+    save_checkpoint, checkpoint_dir, is_session_enabled)
 from ray.tune.progress_reporter import (ProgressReporter, CLIReporter,
                                         JupyterNotebookReporter)
 from ray.tune.sample import (function, sample_from, uniform, quniform, choice,
@@ -28,6 +28,7 @@ __all__ = [
     "qrandint", "randn", "qrandn", "loguniform", "qloguniform",
     "ExperimentAnalysis", "Analysis", "CLIReporter", "JupyterNotebookReporter",
     "ProgressReporter", "report", "get_trial_dir", "get_trial_name",
-    "get_trial_id", "make_checkpoint_dir", "save_checkpoint", "checkpoint_dir",
-    "SyncConfig", "create_searcher", "create_scheduler"
+    "get_trial_id", "make_checkpoint_dir", "save_checkpoint",
+    "is_session_enabled", "checkpoint_dir", "SyncConfig", "create_searcher",
+    "create_scheduler"
 ]

python/ray/tune/session.py

@@ -7,6 +7,12 @@ logger = logging.getLogger(__name__)
 _session = None
 
 
+def is_session_enabled() -> bool:
+    """Returns True if running within an Tune process."""
+    global _session
+    return _session is not None
+
+
 def get_session():
     global _session
     if not _session:

python/ray/tune/tests/test_function_api.py

@@ -400,6 +400,18 @@ class FunctionApiTest(unittest.TestCase):
         trial_dfs = list(analysis.trial_dataframes.values())
         assert len(trial_dfs[0]["training_iteration"]) == 10
 
+    def testEnabled(self):
+        def train(config, checkpoint_dir=None):
+            is_active = tune.is_session_enabled()
+            if is_active:
+                tune.report(active=is_active)
+            return is_active
+
+        assert train({}) is False
+        analysis = tune.run(train)
+        t = analysis.trials[0]
+        assert t.last_result["active"]
+
     def testBlankCheckpoint(self):
         def train(config, checkpoint_dir=None):
             restored = bool(checkpoint_dir)