def testExperimentTrackingMetricUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
# update tracking metric
# (should perform update in place)
metric = Metric(name="tracking", lower_is_better=True)
experiment.update_tracking_metric(metric)
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
# add tracking metric
metric = Metric(name="tracking2")
experiment.add_tracking_metric(metric)
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
# remove tracking metric
# (old one should be deleted)
experiment.remove_tracking_metric("tracking2")
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentRunnerUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
# one runner on the batch
self.assertEqual(get_session().query(SQARunner).count(), 1)
# add runner to experiment
runner = get_synthetic_runner()
experiment.runner = runner
save_experiment(experiment)
self.assertEqual(get_session().query(SQARunner).count(), 2)
# update runner
# (should perform update in place)
runner = get_synthetic_runner()
runner.dummy_metadata = {"foo": "bar"}
experiment.runner = runner
save_experiment(experiment)
self.assertEqual(get_session().query(SQARunner).count(), 2)
# remove runner
# (old one should be deleted)
experiment.runner = None
save_experiment(experiment)
self.assertEqual(get_session().query(SQARunner).count(), 1)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentGeneratorRunUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
# one main generator run, one for the status quo
self.assertEqual(get_session().query(SQAGeneratorRun).count(), 2)
# add a arm
# this will create one wrapper generator run
# this will also replace the status quo generator run,
# since the weight of the status quo will have changed
trial = experiment.trials[0]
trial.add_arm(get_arm())
save_experiment(experiment)
self.assertEqual(get_session().query(SQAGeneratorRun).count(), 3)
generator_run = get_generator_run() # TODO[Lena, T46190605]: remove
generator_run._model_key = None
generator_run._model_kwargs = None
generator_run._bridge_kwargs = None
trial.add_generator_run(generator_run=generator_run, multiplier=0.5)
save_experiment(experiment)
self.assertEqual(get_session().query(SQAGeneratorRun).count(), 4)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
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)
def testExperimentAbandonedArmUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
# one arm is already abandoned
self.assertEqual(get_session().query(SQAAbandonedArm).count(), 1)
trial = experiment.trials[0]
trial.mark_arm_abandoned(trial.arms[1].name)
save_experiment(experiment)
self.assertEqual(get_session().query(SQAAbandonedArm).count(), 2)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentParameterUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameter).count(),
len(experiment.search_space.parameters),
)
# update a parameter
# (should perform update in place)
search_space = get_search_space()
parameter = get_choice_parameter()
parameter.add_values(["foobar"])
search_space.update_parameter(parameter)
experiment.search_space = search_space
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameter).count(),
len(experiment.search_space.parameters),
)
# add a parameter
parameter = RangeParameter(name="x1",
parameter_type=ParameterType.FLOAT,
lower=-5,
upper=10)
search_space.add_parameter(parameter)
experiment.search_space = search_space
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameter).count(),
len(experiment.search_space.parameters),
)
# remove a parameter
# (old one should be deleted)
del search_space._parameters["x1"]
experiment.search_space = search_space
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameter).count(),
len(experiment.search_space.parameters),
)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(get_session().query(SQAExperiment).count(), 1)
# update experiment
# (should perform update in place)
experiment.description = "foobar"
save_experiment(experiment)
self.assertEqual(get_session().query(SQAExperiment).count(), 1)
experiment.status_quo = Arm(parameters={"w": 0.0, "x": 1, "y": "y", "z": True})
save_experiment(experiment)
self.assertEqual(get_session().query(SQAExperiment).count(), 1)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentTrialUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(get_session().query(SQATrial).count(), 1)
self.assertEqual(get_session().query(SQARunner).count(), 1)
# add trial
trial = experiment.new_batch_trial()
runner = get_synthetic_runner()
trial.runner = runner
save_experiment(experiment)
self.assertEqual(get_session().query(SQATrial).count(), 2)
self.assertEqual(get_session().query(SQARunner).count(), 2)
# update trial's runner
runner.dummy_metadata = "dummy metadata"
trial.runner = runner
save_experiment(experiment)
self.assertEqual(get_session().query(SQATrial).count(), 2)
self.assertEqual(get_session().query(SQARunner).count(), 2)
trial.run()
save_experiment(experiment)
self.assertEqual(get_session().query(SQATrial).count(), 2)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentParameterConstraintUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameterConstraint).count(), # 3
len(experiment.search_space.parameter_constraints), # 3
)
# add a parameter constraint
search_space = experiment.search_space
existing_constraint = experiment.search_space.parameter_constraints[0]
new_constraint = get_sum_constraint2()
search_space.add_parameter_constraints([new_constraint])
experiment.search_space = search_space
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameterConstraint).count(),
len(experiment.search_space.parameter_constraints),
)
# update a parameter constraint
# (since we don't have UIDs for these, we throw out the old one
# and create a new one)
new_constraint.bound = 5.0
search_space.set_parameter_constraints(
[existing_constraint, new_constraint])
experiment.search_space = search_space
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameterConstraint).count(),
len(experiment.search_space.parameter_constraints),
)
# remove a parameter constraint
# (old one should be deleted)
search_space.set_parameter_constraints([new_constraint])
experiment.search_space = search_space
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAParameterConstraint).count(),
len(experiment.search_space.parameter_constraints),
)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentObjectiveThresholdUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(),
len(experiment.metrics))
# update objective threshold
# (should perform update in place)
optimization_config = get_multi_objective_optimization_config()
objective_threshold = get_objective_threshold()
optimization_config.objective_thresholds = [objective_threshold]
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(), 6)
# add outcome constraint
outcome_constraint2 = OutcomeConstraint(metric=Metric(name="outcome"),
op=ComparisonOp.GEQ,
bound=-0.5)
optimization_config.outcome_constraints = [
optimization_config.outcome_constraints[0],
outcome_constraint2,
]
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(), 7)
# remove outcome constraint
# (old one should become tracking metric)
optimization_config.outcome_constraints = []
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(), 5)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
# Optimization config should correctly reload even with no
# objective_thresholds
optimization_config.objective_thresholds = []
save_experiment(experiment)
self.assertEqual(get_session().query(SQAMetric).count(), 4)
loaded_experiment = load_experiment(experiment.name)
self.assertEqual(experiment, loaded_experiment)
def testExperimentOutcomeConstraintUpdates(self):
experiment = get_experiment_with_batch_trial()
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAMetric).count(), len(experiment.metrics)
)
# update outcome constraint
# (should perform update in place)
optimization_config = get_optimization_config()
outcome_constraint = get_outcome_constraint()
outcome_constraint.bound = -1.0
optimization_config.outcome_constraints = [outcome_constraint]
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAMetric).count(), len(experiment.metrics)
)
# add outcome constraint
outcome_constraint2 = OutcomeConstraint(
metric=Metric(name="outcome"), op=ComparisonOp.GEQ, bound=-0.5
)
optimization_config.outcome_constraints = [
outcome_constraint,
outcome_constraint2,
]
experiment.optimization_config = optimization_config
save_experiment(experiment)
self.assertEqual(
get_session().query(SQAMetric).count(), len(experiment.metrics)
)
# remove outcome constraint
# (old one should become tracking metric)
optimization_config.outcome_constraints = [outcome_constraint]
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)
