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Sven
60d4d5e1aa
* Remove all __future__ imports from RLlib. * Remove (object) again from tf_run_builder.py::TFRunBuilder. * Fix 2xLINT warnings. * Fix broken appo_policy import (must be appo_tf_policy) * Remove future imports from all other ray files (not just RLlib). * Remove future imports from all other ray files (not just RLlib). * Remove future import blocks that contain `unicode_literals` as well. Revert appo_tf_policy.py to appo_policy.py (belongs to another PR). * Add two empty lines before Schedule class. * Put back __future__ imports into determine_tests_to_run.py. Fails otherwise on a py2/print related error.
72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
import random
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import unittest
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from ray.tune import register_trainable
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from ray.tune.automl import SearchSpace, DiscreteSpace, GridSearch
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class AutoMLSearcherTest(unittest.TestCase):
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def setUp(self):
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def dummy_train(config, reporter):
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reporter(timesteps_total=100, done=True)
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register_trainable("f1", dummy_train)
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def testExpandSearchSpace(self):
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exp = {"test-exp": {"run": "f1", "config": {"a": {"d": "dummy"}}}}
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space = SearchSpace([
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DiscreteSpace("a.b.c", [1, 2]),
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DiscreteSpace("a.d", ["a", "b"]),
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])
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searcher = GridSearch(space, "reward")
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searcher.add_configurations(exp)
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trials = searcher.next_trials()
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self.assertEqual(len(trials), 4)
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self.assertTrue(trials[0].config["a"]["b"]["c"] in [1, 2])
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self.assertTrue(trials[1].config["a"]["d"] in ["a", "b"])
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def testSearchRound(self):
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exp = {"test-exp": {"run": "f1", "config": {"a": {"d": "dummy"}}}}
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space = SearchSpace([
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DiscreteSpace("a.b.c", [1, 2]),
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DiscreteSpace("a.d", ["a", "b"]),
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])
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searcher = GridSearch(space, "reward")
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searcher.add_configurations(exp)
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trials = searcher.next_trials()
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self.assertEqual(len(searcher.next_trials()), 0)
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for trial in trials[1:]:
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searcher.on_trial_complete(trial.trial_id)
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searcher.on_trial_complete(trials[0].trial_id, error=True)
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self.assertTrue(searcher.is_finished())
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def testBestTrial(self):
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exp = {"test-exp": {"run": "f1", "config": {"a": {"d": "dummy"}}}}
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space = SearchSpace([
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DiscreteSpace("a.b.c", [1, 2]),
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DiscreteSpace("a.d", ["a", "b"]),
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])
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searcher = GridSearch(space, "reward")
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searcher.add_configurations(exp)
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trials = searcher.next_trials()
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self.assertEqual(len(searcher.next_trials()), 0)
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for i, trial in enumerate(trials):
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rewards = list(range(i, i + 10))
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random.shuffle(rewards)
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for reward in rewards:
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searcher.on_trial_result(trial.trial_id, {"reward": reward})
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best_trial = searcher.get_best_trial()
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self.assertEqual(best_trial, trials[-1])
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self.assertEqual(best_trial.best_result["reward"], 3 + 10 - 1)
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if __name__ == "__main__":
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import pytest
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import sys
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sys.exit(pytest.main(["-v", __file__]))
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