chore: import upstream snapshot with attribution

python/ray/tune/tests/test_experiment.py

@@ -0,0 +1,117 @@
+import threading
+import unittest
+
+import ray
+from ray.tune import CheckpointConfig, register_trainable
+from ray.tune.error import TuneError
+from ray.tune.experiment import Experiment, _convert_to_experiment_list
+from ray.tune.utils import diagnose_serialization
+
+
+class ExperimentTest(unittest.TestCase):
+    def tearDown(self):
+        ray.shutdown()
+
+    def setUp(self):
+        def train_fn(config):
+            for i in range(100):
+                ray.tune.report(dict(timesteps_total=i))
+
+        register_trainable("f1", train_fn)
+
+    def testConvertExperimentFromExperiment(self):
+        exp1 = Experiment(
+            **{"name": "foo", "run": "f1", "config": {"script_min_iter_time_s": 0}}
+        )
+        result = _convert_to_experiment_list(exp1)
+        self.assertEqual(len(result), 1)
+        self.assertEqual(type(result), list)
+
+    def testConvertExperimentNone(self):
+        result = _convert_to_experiment_list(None)
+        self.assertEqual(len(result), 0)
+        self.assertEqual(type(result), list)
+
+    def testConvertExperimentList(self):
+        exp1 = Experiment(
+            **{"name": "foo", "run": "f1", "config": {"script_min_iter_time_s": 0}}
+        )
+        result = _convert_to_experiment_list([exp1, exp1])
+        self.assertEqual(len(result), 2)
+        self.assertEqual(type(result), list)
+
+    def testConvertExperimentJSON(self):
+        experiment = {
+            "name": {"run": "f1", "config": {"script_min_iter_time_s": 0}},
+            "named": {"run": "f1", "config": {"script_min_iter_time_s": 0}},
+        }
+        result = _convert_to_experiment_list(experiment)
+        self.assertEqual(len(result), 2)
+        self.assertEqual(type(result), list)
+
+    def testConvertExperimentIncorrect(self):
+        self.assertRaises(TuneError, lambda: _convert_to_experiment_list("hi"))
+
+    def testFuncTrainableCheckpointConfigValidation(self):
+        """Raise an error when trying to specify checkpoint_at_end/checkpoint_frequency
+        with a function trainable."""
+        with self.assertRaises(ValueError):
+            Experiment(
+                name="foo",
+                run="f1",  # Will point to a wrapped function trainable
+                checkpoint_config=CheckpointConfig(checkpoint_at_end=True),
+            )
+        with self.assertRaises(ValueError):
+            Experiment(
+                name="foo",
+                run="f1",
+                checkpoint_config=CheckpointConfig(checkpoint_frequency=1),
+            )
+        with self.assertRaises(ValueError):
+            Experiment(
+                name="foo",
+                run=lambda config: 1,
+                checkpoint_config=CheckpointConfig(checkpoint_at_end=True),
+            )
+
+    def testInvalidExperimentConfig(self):
+        with self.assertRaises(ValueError):
+            Experiment(name="foo", run="f1", config="invalid")
+
+        class InvalidClass:
+            def to_dict(self):
+                return {"valid": 1}
+
+        with self.assertRaises(ValueError):
+            Experiment(name="foo", run="f1", config=InvalidClass())
+
+        Experiment(name="foo", run="f1", config=InvalidClass().to_dict())
+
+
+class ValidateUtilTest(unittest.TestCase):
+    def testDiagnoseSerialization(self):
+        # this is not serializable
+        e = threading.Event()
+
+        def test(config):
+            print(e)
+
+        assert diagnose_serialization(test) is not True
+
+        # should help identify that 'e' should be moved into
+        # the `test` scope.
+
+        # correct implementation
+        def test(config):
+            e = threading.Event()
+            print(e)
+
+        assert diagnose_serialization(test) is True
+
+
+if __name__ == "__main__":
+    import sys
+
+    import pytest
+
+    sys.exit(pytest.main(["-v", __file__]))