def test_MTGP(self):
"""Tests MTGP instantiation."""
# Test Multi-type MTGP
exp = get_multi_type_experiment(add_trials=True)
mtgp = get_MTGP(experiment=exp, data=exp.fetch_data())
self.assertIsInstance(mtgp, TorchModelBridge)
# Test Single-type MTGP
exp = get_branin_experiment()
# Check that factory generates a valid sobol modelbridge.
sobol = get_sobol(search_space=exp.search_space)
self.assertIsInstance(sobol, RandomModelBridge)
for _ in range(5):
sobol_run = sobol.gen(n=1)
t = exp.new_batch_trial().add_generator_run(sobol_run)
t.set_status_quo_with_weight(status_quo=t.arms[0], weight=0.5)
t.run()
mtgp = get_MTGP(experiment=exp, data=exp.fetch_data(), trial_index=0)
self.assertIsInstance(mtgp, TorchModelBridge)
with self.assertRaises(ValueError):
get_MTGP(experiment=exp, data=exp.fetch_data(), trial_index=9)
exp = get_branin_experiment()
sobol = get_sobol(search_space=exp.search_space)
self.assertIsInstance(sobol, RandomModelBridge)
sobol_run = sobol.gen(n=1)
t = exp.new_batch_trial().add_generator_run(sobol_run)
t.run()
with self.assertRaises(ValueError):
get_MTGP(experiment=exp, data=exp.fetch_data(), trial_index=0)
def setUp(self):
self.experiment = get_multi_type_experiment(add_trials=True)
self.data = self.experiment.fetch_data()
self.observations = observations_from_data(self.experiment, self.data)
self.observation_data = [o.data for o in self.observations]
self.observation_features = [o.features for o in self.observations]
self.tconfig = tconfig_from_mt_experiment(self.experiment)
def testEq(self):
exp2 = get_multi_type_experiment()
# Should be equal to start
self.assertTrue(self.experiment == exp2)
self.experiment.add_tracking_metric(BraninMetric("m3", ["x2", "x1"]),
trial_type="type1",
canonical_name="m4")
# Test different set of metrics
self.assertFalse(self.experiment == exp2)
exp2.add_tracking_metric(BraninMetric("m3", ["x2", "x1"]),
trial_type="type1",
canonical_name="m5")
# Test different metric definitions
self.assertFalse(self.experiment == exp2)
exp2.update_tracking_metric(BraninMetric("m3", ["x2", "x1"]),
trial_type="type1",
canonical_name="m4")
# Should be the same
self.assertTrue(self.experiment == exp2)
exp2.remove_tracking_metric("m3")
self.assertFalse(self.experiment == exp2)
def testMTExperimentSaveAndLoad(self):
experiment = get_multi_type_experiment(add_trials=True)
save_experiment(experiment)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(loaded_experiment.default_trial_type, "type1")
self.assertEqual(len(loaded_experiment._trial_type_to_runner), 2)
self.assertEqual(loaded_experiment.metric_to_trial_type["m1"], "type1")
self.assertEqual(loaded_experiment.metric_to_trial_type["m2"], "type2")
self.assertEqual(loaded_experiment._metric_to_canonical_name["m2"], "m1")
self.assertEqual(len(loaded_experiment.trials), 2)
def test_MTGP(self):
"""Tests MTGP instantiation."""
# Test Multi-type MTGP
exp = get_multi_type_experiment(add_trials=True)
mtgp = get_MTGP(experiment=exp, data=exp.fetch_data())
self.assertIsInstance(mtgp, TorchModelBridge)
# Test Single-type MTGP
exp = get_branin_experiment()
# Check that factory generates a valid sobol modelbridge.
sobol = get_sobol(search_space=exp.search_space)
self.assertIsInstance(sobol, RandomModelBridge)
for _ in range(5):
sobol_run = sobol.gen(n=1)
exp.new_batch_trial().add_generator_run(sobol_run).run()
mtgp = get_MTGP(experiment=exp, data=exp.fetch_data())
self.assertIsInstance(mtgp, TorchModelBridge)
def test_MTGP(self):
"""Tests MTGP instantiation."""
# Test Multi-type MTGP
exp = get_multi_type_experiment(add_trials=True)
mtgp = get_MTGP(experiment=exp, data=exp.fetch_data())
self.assertIsInstance(mtgp, TorchModelBridge)
# Test Single-type MTGP
exp = get_branin_experiment()
# Check that factory generates a valid sobol modelbridge.
sobol = get_sobol(search_space=exp.search_space)
self.assertIsInstance(sobol, RandomModelBridge)
for _ in range(5):
sobol_run = sobol.gen(n=1)
exp.new_batch_trial().add_generator_run(sobol_run).run()
mtgp = get_MTGP(experiment=exp,
is_multi_type=False,
data=exp.fetch_data())
self.assertIsInstance(mtgp, TorchModelBridge)
# Test wrong call of Multi-type MTGP. The type of the input experiment
# should be MultiTypeExperiment.
with self.assertRaises(ValueError):
get_MTGP(experiment=exp, is_multi_type=True, data=exp.fetch_data())
def setUp(self):
self.experiment = get_multi_type_experiment()
def test_MTGP(self):
"""Tests MTGP instantiation."""
exp = get_multi_type_experiment(add_trials=True)
mtgp = get_MTGP(experiment=exp, data=exp.fetch_data())
self.assertIsInstance(mtgp, TorchModelBridge)
