def testExperimentObjectiveUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
# update objective
# (should perform update in place)
optimization_config = get_optimization_config()
objective = get_objective()
objective.minimize = True
optimization_config.objective = objective
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
# replace objective
# (old one should become tracking metric)
optimization_config.objective = Objective(metric=Metric(
name="objective"))
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
from unittest.mock import patch
import pandas as pd
from ax.core.base_trial import BaseTrial, TrialStatus
from ax.core.data import Data
from ax.core.generator_run import GeneratorRun, GeneratorRunType
from ax.utils.common.testutils import TestCase
from ax.utils.testing.core_stubs import get_arms, get_experiment, get_objective
TEST_DATA = Data(
df=pd.DataFrame(
[
{
"arm_name": "0_0",
"metric_name": get_objective().metric.name,
"mean": 1.0,
"sem": 2.0,
"trial_index": 0,
}
]
)
)
class TrialTest(TestCase):
def setUp(self):
self.experiment = get_experiment()
self.trial = self.experiment.new_trial()
self.arm = get_arms()[0]
self.trial.add_arm(self.arm)
