def testUpdateGenerationStrategy(self):
generation_strategy = get_generation_strategy()
save_generation_strategy(generation_strategy=generation_strategy)
experiment = get_branin_experiment()
generation_strategy = get_generation_strategy()
save_experiment(experiment)
# add generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(experiment))
save_generation_strategy(generation_strategy=generation_strategy)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name
)
# `_seen_trial_indices_by_status` attribute of a GS is not saved in DB,
# so it will be None in the restored version of the GS.
# Hackily removing it from the original GS to check equality.
generation_strategy._seen_trial_indices_by_status = None
self.assertEqual(generation_strategy, loaded_generation_strategy)
# add another generator run, save, reload
experiment.new_trial(
generator_run=generation_strategy.gen(experiment, data=get_branin_data())
)
save_generation_strategy(generation_strategy=generation_strategy)
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name
)
# `_seen_trial_indices_by_status` attribute of a GS is not saved in DB,
# so it will be None in the restored version of the GS.
# Hackily removing it from the original GS to check equality.
generation_strategy._seen_trial_indices_by_status = None
self.assertEqual(generation_strategy, loaded_generation_strategy)
# make sure that we can update the experiment too
experiment.description = "foobar"
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name
)
self.assertEqual(generation_strategy, loaded_generation_strategy)
self.assertEqual(
generation_strategy._experiment.description, experiment.description
)
self.assertEqual(
generation_strategy._experiment.description,
loaded_generation_strategy._experiment.description,
)
def testUpdateGenerationStrategy(self):
generation_strategy = get_generation_strategy()
save_generation_strategy(generation_strategy=generation_strategy)
# Add data, save, reload
generation_strategy._data = Data(
df=pd.DataFrame.from_records([{
"metric_name": "foo",
"mean": 1,
"arm_name": "bar"
}]))
save_generation_strategy(generation_strategy=generation_strategy)
loaded_generation_strategy = load_generation_strategy_by_id(
gs_id=generation_strategy._db_id)
self.assertEqual(generation_strategy, loaded_generation_strategy)
experiment = get_branin_experiment()
generation_strategy = get_generation_strategy()
save_experiment(experiment)
# add generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(experiment))
save_generation_strategy(generation_strategy=generation_strategy)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
# add another generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(
experiment, new_data=get_branin_data()))
save_generation_strategy(generation_strategy=generation_strategy)
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
# make sure that we can update the experiment too
experiment.description = "foobar"
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
self.assertEqual(generation_strategy._experiment.description,
experiment.description)
self.assertEqual(
generation_strategy._experiment.description,
loaded_generation_strategy._experiment.description,
)
def testUpdateGenerationStrategyIncrementally(self):
experiment = get_branin_experiment()
generation_strategy = choose_generation_strategy(
experiment.search_space)
save_experiment(experiment=experiment)
save_generation_strategy(generation_strategy=generation_strategy)
# add generator runs, save, reload
generator_runs = []
for i in range(7):
data = get_branin_data() if i > 0 else None
gr = generation_strategy.gen(experiment, data=data)
generator_runs.append(gr)
trial = experiment.new_trial(generator_run=gr).mark_running(
no_runner_required=True)
trial.mark_completed()
save_experiment(experiment=experiment)
update_generation_strategy(generation_strategy=generation_strategy,
generator_runs=generator_runs)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy._curr.index,
loaded_generation_strategy._curr.index, 1)
self.assertEqual(len(loaded_generation_strategy._generator_runs), 7)
def testEncodeDecodeGenerationStrategy(self):
# Cannot load generation strategy before it has been saved
with self.assertRaises(ValueError):
load_generation_strategy_by_id(gs_id=0)
# Check that we can encode and decode the generation strategy *before*
# it has generated some trials and been updated with some data.
generation_strategy = get_generation_strategy()
# Check that we can save a generation strategy without an experiment
# attached.
save_generation_strategy(generation_strategy=generation_strategy)
# Also try restoring this generation strategy by its ID in the DB.
new_generation_strategy = load_generation_strategy_by_id(
gs_id=generation_strategy._db_id
)
self.assertEqual(generation_strategy, new_generation_strategy)
self.assertIsNone(generation_strategy._experiment)
# Cannot load generation strategy before it has been saved
experiment = get_branin_experiment()
save_experiment(experiment)
with self.assertRaises(ValueError):
load_generation_strategy_by_experiment_name(experiment_name=experiment.name)
# Check that we can encode and decode the generation strategy *after*
# it has generated some trials and been updated with some data.
generation_strategy = new_generation_strategy
experiment.new_trial(generation_strategy.gen(experiment=experiment))
experiment.new_trial(
generation_strategy.gen(experiment, data=get_branin_data())
)
save_generation_strategy(generation_strategy=generation_strategy)
save_experiment(experiment)
# Try restoring the generation strategy using the experiment its
# attached to.
new_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name
)
# `_seen_trial_indices_by_status` attribute of a GS is not saved in DB,
# so it will be None in the restored version of the GS.
# Hackily removing it from the original GS to check equality.
generation_strategy._seen_trial_indices_by_status = None
self.assertEqual(generation_strategy, new_generation_strategy)
self.assertIsInstance(new_generation_strategy._steps[0].model, Models)
self.assertIsInstance(new_generation_strategy.model, ModelBridge)
self.assertEqual(len(new_generation_strategy._generator_runs), 2)
self.assertEqual(new_generation_strategy._experiment._name, experiment._name)
def testEncodeDecodeGenerationStrategy(self):
# Cannot load generation strategy before it has been saved
with self.assertRaises(ValueError):
load_generation_strategy_by_id(gs_id=0)
# Check that we can encode and decode the generation strategy *before*
# it has generated some trials and been updated with some data.
generation_strategy = get_generation_strategy()
# Check that we can save a generation strategy without an experiment
# attached.
save_generation_strategy(generation_strategy=generation_strategy)
# Also try restoring this generation strategy by its ID in the DB.
new_generation_strategy = load_generation_strategy_by_id(
gs_id=generation_strategy._db_id)
self.assertEqual(generation_strategy, new_generation_strategy)
self.assertIsNone(generation_strategy._experiment)
self.assertEqual(len(generation_strategy._generated), 0)
self.assertEqual(len(generation_strategy._observed), 0)
# Cannot load generation strategy before it has been saved
experiment = get_branin_experiment()
save_experiment(experiment)
with self.assertRaises(ValueError):
load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
# Check that we can encode and decode the generation strategy *after*
# it has generated some trials and been updated with some data.
generation_strategy = new_generation_strategy
experiment.new_trial(generator_run=generation_strategy.gen(experiment))
experiment.new_trial(
generation_strategy.gen(experiment, new_data=get_branin_data()))
self.assertGreater(len(generation_strategy._generated), 0)
self.assertGreater(len(generation_strategy._observed), 0)
save_generation_strategy(generation_strategy=generation_strategy)
save_experiment(experiment)
# Try restoring the generation strategy using the experiment its
# attached to.
new_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, new_generation_strategy)
self.assertIsInstance(new_generation_strategy._steps[0].model, Models)
self.assertIsInstance(new_generation_strategy.model, ModelBridge)
self.assertEqual(len(new_generation_strategy._generator_runs), 2)
self.assertEqual(new_generation_strategy._experiment._name,
experiment._name)
def testUpdateGenerationStrategy(self):
generation_strategy = get_generation_strategy()
save_generation_strategy(generation_strategy=generation_strategy)
experiment = get_branin_experiment()
generation_strategy = get_generation_strategy()
save_experiment(experiment)
# add generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(experiment))
save_generation_strategy(generation_strategy=generation_strategy)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
# add another generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(
experiment, data=get_branin_data()))
save_generation_strategy(generation_strategy=generation_strategy)
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
# During restoration of generation strategy's model from its last generator
# run, we set `_seen_trial_indices_by_status` to that of the experiment,
# from which we are grabbing the data to restore the model with. When the
# experiment was updated more recently than the last `gen` from generation
# strategy, the generation strategy prior to save might not have 'seen'
# some recently added trials, so we update the mappings to match and check
# that the generation strategies are equal otherwise.
generation_strategy._seen_trial_indices_by_status[
TrialStatus.CANDIDATE].add(1)
self.assertEqual(generation_strategy, loaded_generation_strategy)
# make sure that we can update the experiment too
experiment.description = "foobar"
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
self.assertEqual(generation_strategy._experiment.description,
experiment.description)
self.assertEqual(
generation_strategy._experiment.description,
loaded_generation_strategy._experiment.description,
)
def testUpdateGenerationStrategy(self):
generation_strategy = get_generation_strategy()
save_generation_strategy(generation_strategy=generation_strategy)
experiment = get_branin_experiment()
generation_strategy = get_generation_strategy()
save_experiment(experiment)
# add generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(experiment))
save_generation_strategy(generation_strategy=generation_strategy)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
# add another generator run, save, reload
experiment.new_trial(generator_run=generation_strategy.gen(
experiment, data=get_branin_data()))
save_generation_strategy(generation_strategy=generation_strategy)
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
# make sure that we can update the experiment too
experiment.description = "foobar"
save_experiment(experiment)
loaded_generation_strategy = load_generation_strategy_by_experiment_name(
experiment_name=experiment.name)
self.assertEqual(generation_strategy, loaded_generation_strategy)
self.assertEqual(generation_strategy._experiment.description,
experiment.description)
self.assertEqual(
generation_strategy._experiment.description,
loaded_generation_strategy._experiment.description,
)
