[tune] Fix SearchAlg finishing early (#3081)

* Fix trial search alg finishing early

* Fix lint

* fix lint

* nit fix

doc/source/tune-usage.rst

@@ -223,7 +223,7 @@ For TensorFlow model training, this would look something like this `(full tensor
 .. code-block:: python
 
     class MyClass(Trainable):
-        def _setup(self):
+        def _setup(self, config):
             self.saver = tf.train.Saver()
             self.sess = ...
             self.iteration = 0

python/ray/tune/test/trial_runner_test.py

@@ -20,7 +20,8 @@ from ray.tune.experiment import Experiment
 from ray.tune.trial import Trial, Resources
 from ray.tune.trial_runner import TrialRunner
 from ray.tune.suggest import grid_search, BasicVariantGenerator
-from ray.tune.suggest.suggestion import _MockSuggestionAlgorithm
+from ray.tune.suggest.suggestion import (_MockSuggestionAlgorithm,
+                                         SuggestionAlgorithm)
 from ray.tune.suggest.variant_generator import RecursiveDependencyError
 
 
@@ -1385,6 +1386,31 @@ class TrialRunnerTest(unittest.TestCase):
         self.assertTrue(searcher.is_finished())
         self.assertTrue(runner.is_finished())
 
+    def testSearchAlgFinishes(self):
+        """SearchAlg changing state in `next_trials` does not crash."""
+
+        class FinishFastAlg(SuggestionAlgorithm):
+            def next_trials(self):
+                self._finished = True
+                return []
+
+        ray.init(num_cpus=4, num_gpus=2)
+        experiment_spec = {
+            "run": "__fake",
+            "num_samples": 3,
+            "stop": {
+                "training_iteration": 1
+            }
+        }
+        searcher = FinishFastAlg()
+        experiments = [Experiment.from_json("test", experiment_spec)]
+        searcher.add_configurations(experiments)
+
+        runner = TrialRunner(search_alg=searcher)
+        runner.step()  # This should not fail
+        self.assertTrue(searcher.is_finished())
+        self.assertTrue(runner.is_finished())
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=2)

python/ray/tune/trial_runner.py

@@ -114,6 +114,10 @@ class TrialRunner(object):
             self.trial_executor.start_trial(next_trial)
         elif self.trial_executor.get_running_trials():
             self._process_events()
+        elif self.is_finished():
+            # We check `is_finished` again here because the experiment
+            # may have finished while getting the next trial.
+            pass
         else:
             for trial in self._trials:
                 if trial.status == Trial.PENDING: