[tune] refactor and add examples (#11931)

python/ray/tune/tests/_test_cluster_interrupt_searcher.py

@@ -2,7 +2,7 @@ import os
 import argparse
 
 from ray.tune import run
-from ray.tune.examples.async_hyperband_example import MyTrainableClass
+from ray.tune.utils._mock_trainable import MyTrainableClass
 from ray.tune.suggest.hyperopt import HyperOptSearch
 from ray.tune.suggest.suggestion import ConcurrencyLimiter
 

python/ray/tune/tests/test_cluster.py

@@ -25,6 +25,7 @@ from ray.tune.syncer import CloudSyncer, SyncerCallback, get_node_syncer
 from ray.tune.utils.trainable import TrainableUtil
 from ray.tune.trial import Trial
 from ray.tune.trial_runner import TrialRunner
+from ray.tune.utils._mock_trainable import MyTrainableClass
 from ray.tune.utils.mock import (MockDurableTrainer, MockRemoteTrainer,
                                  MockNodeSyncer, mock_storage_client,
                                  MOCK_REMOTE_DIR)
@@ -746,7 +747,6 @@ def test_cluster_interrupt_searcher(start_connected_cluster, tmpdir):
     cluster = start_connected_cluster
     dirpath = str(tmpdir)
     local_checkpoint_dir = os.path.join(dirpath, "experiment")
-    from ray.tune.examples.async_hyperband_example import MyTrainableClass
     from ray.tune import register_trainable
     register_trainable("trainable", MyTrainableClass)
 
@@ -770,6 +770,8 @@ def test_cluster_interrupt_searcher(start_connected_cluster, tmpdir):
             if trials and len(trials) >= 10:
                 break
         time.sleep(.5)
+    else:
+        raise ValueError(f"Didn't generate enough trials: {len(trials)}")
 
     if not TrialRunner.checkpoint_exists(local_checkpoint_dir):
         raise RuntimeError(
@@ -792,8 +794,10 @@ def test_cluster_interrupt_searcher(start_connected_cluster, tmpdir):
             runner = TrialRunner(
                 resume="LOCAL", local_checkpoint_dir=local_checkpoint_dir)
             trials = runner.get_trials()
+
             if len(trials) == 0:
                 continue  # nonblocking script hasn't resumed yet, wait
+
             reached = True
             assert len(trials) >= 10
             assert len(trials) <= 20

python/ray/tune/tests/test_experiment_analysis.py

@@ -8,7 +8,7 @@ from numpy import nan
 
 import ray
 from ray import tune
-from ray.tune.examples.async_hyperband_example import MyTrainableClass
+from ray.tune.utils.mock import MyTrainableClass
 
 
 class ExperimentAnalysisSuite(unittest.TestCase):

python/ray/tune/tests/test_experiment_analysis_mem.py

@@ -11,7 +11,7 @@ import numpy as np
 import ray
 from ray.tune import (run, Trainable, sample_from, Analysis,
                       ExperimentAnalysis, grid_search)
-from ray.tune.examples.async_hyperband_example import MyTrainableClass
+from ray.tune.utils.mock import MyTrainableClass
 
 
 class ExperimentAnalysisInMemorySuite(unittest.TestCase):

python/ray/tune/tests/test_tune_restore.py

@@ -116,7 +116,7 @@ class TuneExampleTest(unittest.TestCase):
         validate_save_restore(MyTrainableClass, use_object_store=True)
 
     def testAsyncHyperbandExample(self):
-        from ray.tune.examples.async_hyperband_example import MyTrainableClass
+        from ray.tune.utils.mock import MyTrainableClass
         validate_save_restore(MyTrainableClass)
         validate_save_restore(MyTrainableClass, use_object_store=True)