def test_validate_early_stopping_strategy(self):
class DummyEarlyStoppingStrategy(BaseEarlyStoppingStrategy):
def should_stop_trials_early(
self,
trial_indices: Set[int],
experiment: Experiment,
**kwargs: Dict[str, Any],
) -> Set[int]:
return {}
with patch(
f"{BraninMetric.__module__}.BraninMetric.is_available_while_running",
return_value=False,
), self.assertRaises(ValueError):
Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
early_stopping_strategy=DummyEarlyStoppingStrategy()),
)
# should not error
Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
early_stopping_strategy=DummyEarlyStoppingStrategy()),
)
def test_init(self):
with self.assertRaisesRegex(UnsupportedError,
".* metrics .* implemented fetching"):
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment_no_impl_metrics,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(total_trials=10),
)
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
total_trials=0,
tolerated_trial_failure_rate=0.2,
init_seconds_between_polls=10,
),
)
self.assertEqual(scheduler.experiment, self.branin_experiment)
self.assertEqual(scheduler.generation_strategy, self.sobol_GPEI_GS)
self.assertEqual(scheduler.options.total_trials, 0)
self.assertEqual(scheduler.options.tolerated_trial_failure_rate, 0.2)
self.assertEqual(scheduler.options.init_seconds_between_polls, 10)
self.assertIsNone(scheduler._latest_optimization_start_timestamp)
for status_prop in ExperimentStatusProperties:
self.assertEqual(
scheduler.experiment._properties[status_prop.value], [])
scheduler.run_all_trials() # Runs no trials since total trials is 0.
# `_latest_optimization_start_timestamp` should be set now.
self.assertLessEqual(
scheduler._latest_optimization_start_timestamp,
current_timestamp_in_millis(),
)
def test_run_trials_in_batches(self):
with self.assertRaisesRegex(UnsupportedError,
"only if `poll_available_capacity`"):
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0,
run_trials_in_batches=True,
),
)
scheduler.run_n_trials(max_trials=3)
class PollAvailableCapacityScheduler(BareBonesTestScheduler):
def poll_available_capacity(self):
return 2
scheduler = PollAvailableCapacityScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0,
run_trials_in_batches=True,
),
)
with patch.object(scheduler,
"run_trials",
side_effect=scheduler.run_trials) as mock_run_trials:
scheduler.run_n_trials(max_trials=3)
# Trials should be dispatched twice, as total of three trials
# should be dispatched but capacity is limited to 2.
self.assertEqual(mock_run_trials.call_count, ceil(3 / 2))
def test_repr(self):
scheduler = Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
total_trials=0,
tolerated_trial_failure_rate=0.2,
init_seconds_between_polls=10,
),
)
self.assertEqual(
f"{scheduler}",
("Scheduler(experiment=Experiment(branin_test_experiment), "
"generation_strategy=GenerationStrategy(name='Sobol+GPEI', "
"steps=[Sobol for 5 trials, GPEI for subsequent trials]), "
"options=SchedulerOptions(max_pending_trials=10, "
"trial_type=<class 'ax.core.trial.Trial'>, "
"total_trials=0, tolerated_trial_failure_rate=0.2, "
"min_failed_trials_for_failure_rate_check=5, log_filepath=None, "
"logging_level=20, ttl_seconds_for_trials=None, init_seconds_between_"
"polls=10, min_seconds_before_poll=1.0, seconds_between_polls_backoff_"
"factor=1.5, run_trials_in_batches=False, "
"debug_log_run_metadata=False, early_stopping_strategy=None, "
"suppress_storage_errors_after_retries=False))"),
)
def test_run_trials_and_yield_results_with_early_stopper(self):
total_trials = 3
self.branin_experiment.runner = InfinitePollRunner()
scheduler = EarlyStopsInsteadOfNormalCompletionScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(init_seconds_between_polls=0.1, ),
)
# All trials should be marked complete after one run.
with patch.object(
scheduler,
"should_stop_trials_early",
wraps=scheduler.should_stop_trials_early,
) as mock_should_stop_trials_early, patch.object(
scheduler, "stop_trial_runs",
return_value=None) as mock_stop_trial_runs:
res_list = list(
scheduler.run_trials_and_yield_results(
max_trials=total_trials))
# Two steps complete the experiment given parallelism.
expected_num_polls = 2
self.assertEqual(len(res_list), expected_num_polls + 1)
# Both trials in first batch of parallelism will be early stopped
self.assertEqual(len(res_list[0]["trials_early_stopped_so_far"]),
2)
# Third trial in second batch of parallelism will be early stopped
self.assertEqual(len(res_list[1]["trials_early_stopped_so_far"]),
3)
self.assertEqual(mock_should_stop_trials_early.call_count,
expected_num_polls)
self.assertEqual(mock_stop_trial_runs.call_count,
expected_num_polls)
def test_stop_at_MAX_SECONDS_BETWEEN_POLLS(self):
class InfinitePollScheduler(BareBonesTestScheduler):
def poll_trial_status(self):
return {}
scheduler = InfinitePollScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
total_trials=8,
init_seconds_between_polls=
1, # No wait between polls so test is fast.
),
)
with patch.object(scheduler,
"wait_for_completed_trials_and_report_results",
return_value=None) as mock_await_trials:
scheduler.run_all_trials(timeout_hours=1 / 60 /
15) # 4 second timeout.
# We should be calling `wait_for_completed_trials_and_report_results`
# N = total runtime / `MAX_SECONDS_BETWEEN_POLLS` times.
self.assertEqual(
len(mock_await_trials.call_args),
2, # MAX_SECONDS_BETWEEN_POLLS as patched in decorator
)
def test_get_best_trial(self):
scheduler = Scheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=
0.1, # Short between polls so test is fast.
),
)
self.assertIsNone(scheduler.get_best_parameters())
scheduler.run_n_trials(max_trials=1)
trial, params, _arm = scheduler.get_best_trial()
just_params, _just_arm = scheduler.get_best_parameters()
just_params_unmodeled, _just_arm_unmodled = scheduler.get_best_parameters(
use_model_predictions=False)
with self.assertRaisesRegex(NotImplementedError,
"Please use `get_best_parameters`"):
scheduler.get_pareto_optimal_parameters()
self.assertEqual(trial, 0)
self.assertIn("x1", params)
self.assertIn("x2", params)
self.assertEqual(params, just_params)
self.assertEqual(params, just_params_unmodeled)
def test_run_trials_and_yield_results_with_early_stopper(self):
class EarlyStopsInsteadOfNormalCompletionScheduler(
BareBonesTestScheduler):
def poll_trial_status(self):
return {}
def should_stop_trials_early(self, trial_indices: Set[int]):
return {TrialStatus.COMPLETED: trial_indices}
total_trials = 3
scheduler = EarlyStopsInsteadOfNormalCompletionScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(init_seconds_between_polls=0.1, ),
)
# All trials should be marked complete after one run.
with patch.object(
scheduler,
"should_stop_trials_early",
wraps=scheduler.should_stop_trials_early,
) as mock_should_stop_trials_early:
res_list = list(
scheduler.run_trials_and_yield_results(
max_trials=total_trials))
# Two steps complete the experiment given parallelism.
expected_num_polls = 2
self.assertEqual(len(res_list), expected_num_polls)
self.assertIsInstance(res_list, list)
self.assertDictEqual(
res_list[0],
{"trials_completed_so_far": set(range(total_trials))})
self.assertEqual(mock_should_stop_trials_early.call_count,
expected_num_polls)
def test_run_preattached_trials_only(self):
# assert that pre-attached trials run when max_trials = number of
# pre-attached trials
scheduler = Scheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=
0.1, # Short between polls so test is fast.
),
)
trial = scheduler.experiment.new_trial()
parameter_dict = {"x1": 5, "x2": 5}
trial.add_arm(Arm(parameters=parameter_dict))
with self.assertRaisesRegex(
UserInputError,
"number of pre-attached candidate trials .* is greater than"):
scheduler.run_n_trials(max_trials=0)
scheduler.run_n_trials(max_trials=1)
self.assertEqual(len(scheduler.experiment.trials), 1)
self.assertDictEqual(scheduler.experiment.trials[0].arm.parameters,
parameter_dict)
self.assertTrue( # Make sure all trials got to complete.
all(t.completed_successfully
for t in scheduler.experiment.trials.values()))
def test_validate_early_stopping_strategy(self):
with patch(
f"{BraninMetric.__module__}.BraninMetric.is_available_while_running",
return_value=False,
), self.assertRaises(ValueError):
Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
early_stopping_strategy=DummyEarlyStoppingStrategy()),
)
with patch.object(
OptimizationConfig, "is_moo_problem", return_value=True
), self.assertRaisesRegex(
UnsupportedError,
"Early stopping is not supported on multi-objective problems",
):
Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
early_stopping_strategy=DummyEarlyStoppingStrategy()),
)
with patch(
f"{Scheduler.__module__}.len",
return_value=1,
), self.assertRaisesRegex(
UnsupportedError,
"Early stopping is not supported on problems with outcome constraints.",
):
Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
early_stopping_strategy=DummyEarlyStoppingStrategy()),
)
# should not error
Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
early_stopping_strategy=DummyEarlyStoppingStrategy()),
)
def test_failure_rate(self):
class SchedulerWithFrequentFailedTrials(TestScheduler):
poll_failed_next_time = True
def poll_trial_status(self) -> Dict[TrialStatus, Set[int]]:
running = [t.index for t in self.running_trials]
status = (TrialStatus.FAILED if self.poll_failed_next_time else
TrialStatus.COMPLETED)
# Poll different status next time.
self.poll_failed_next_time = not self.poll_failed_next_time
return {status: {running[randint(0, len(running) - 1)]}}
scheduler = SchedulerWithFrequentFailedTrials(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GS_no_parallelism,
options=SchedulerOptions(
total_trials=8,
tolerated_trial_failure_rate=0.5,
init_seconds_between_polls=
0, # No wait between polls so test is fast.
),
)
scheduler.run_all_trials()
# Trials will have statuses: 0, 2, 4 - FAILED, 1, 3 - COMPLETED. Failure rate
# is 0.5, and we start checking failure rate after first 3 trials.
# Therefore, failure rate should be exceeded after trial #4.
self.assertEqual(len(scheduler.experiment.trials), 5)
# If we set a slightly lower failure rate, it will be reached after 4 trials.
num_preexisting_trials = len(scheduler.experiment.trials)
scheduler = SchedulerWithFrequentFailedTrials(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GS_no_parallelism,
options=SchedulerOptions(
total_trials=8,
tolerated_trial_failure_rate=0.49,
init_seconds_between_polls=
0, # No wait between polls so test is fast.
),
)
self.assertEqual(scheduler._num_preexisting_trials,
num_preexisting_trials)
scheduler.run_all_trials()
self.assertEqual(len(scheduler.experiment.trials),
num_preexisting_trials + 4)
def test_run_multi_arm_generator_run_error(self, mock_gen):
scheduler = TestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(total_trials=1),
)
with self.assertRaisesRegex(SchedulerInternalError, ".* only one was expected"):
scheduler.run_all_trials()
def test_scheduler_with_odd_index_early_stopping_strategy(self):
total_trials = 3
class OddIndexEarlyStoppingStrategy(BaseEarlyStoppingStrategy):
# Trials with odd indices will be early stopped
# Thus, with 3 total trials, trial #1 will be early stopped
def should_stop_trials_early(
self,
trial_indices: Set[int],
experiment: Experiment,
**kwargs: Dict[str, Any],
) -> Dict[int, Optional[str]]:
# Make sure that we can lookup data for the trial,
# even though we won't use it in this dummy strategy
data = experiment.lookup_data(trial_indices=trial_indices)
if data.df.empty:
raise Exception(
f"No data found for trials {trial_indices}; "
"can't determine whether or not to stop early."
)
return {idx: None for idx in trial_indices if idx % 2 == 1}
class SchedulerWithEarlyStoppingStrategy(BareBonesTestScheduler):
poll_trial_status_count = 0
def poll_trial_status(self):
# In the first step, don't complete any trials
# Trial #1 will be early stopped
if self.poll_trial_status_count == 0:
self.poll_trial_status_count += 1
return {}
# In the second step, complete trials 0 and 2
self.poll_trial_status_count += 1
return {TrialStatus.COMPLETED: {0, 2}}
scheduler = SchedulerWithEarlyStoppingStrategy(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0.1,
early_stopping_strategy=OddIndexEarlyStoppingStrategy(),
),
)
with patch.object(
scheduler, "stop_trial_runs", return_value=None
) as mock_stop_trial_runs:
res_list = list(
scheduler.run_trials_and_yield_results(max_trials=total_trials)
)
expected_num_steps = 2
self.assertEqual(len(res_list), expected_num_steps + 1)
# Trial #1 early stopped in first step
self.assertEqual(res_list[0]["trials_early_stopped_so_far"], {1})
# All trials completed by end of second step
self.assertEqual(res_list[1]["trials_early_stopped_so_far"], {1})
self.assertEqual(res_list[1]["trials_completed_so_far"], {0, 2})
self.assertEqual(mock_stop_trial_runs.call_count, expected_num_steps)
def test_base_report_results(self):
self.branin_experiment.runner = NoReportResultsRunner()
scheduler = Scheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(init_seconds_between_polls=0, ),
)
self.assertEqual(scheduler.run_n_trials(max_trials=3),
OptimizationResult())
def test_validate_runners_if_required(self):
# `BareBonesTestScheduler` does not have runner and metrics, so it cannot
# run on experiment that does not specify those (or specifies base Metric,
# which do not implement data-fetching logic).
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(total_trials=10),
)
self.branin_experiment.runner = None
with self.assertRaisesRegex(NotImplementedError, ".* runner is required"):
scheduler.run_all_trials()
def test_optimization_complete(self, _):
# With runners & metrics, `BareBonesTestScheduler.run_all_trials` should run.
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0.1, # Short between polls so test is fast.
),
)
scheduler.run_n_trials(max_trials=1)
# no trials should run if _gen_multiple throws an OptimizationComplete error
self.assertEqual(len(scheduler.experiment.trials), 0)
def test_retries(self):
# Check that retries will be performed for a retriable error.
self.branin_experiment.runner = BrokenRunnerRuntimeError()
scheduler = Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(total_trials=1),
)
# Should raise after 3 retries.
with self.assertRaisesRegex(RuntimeError, ".* testing .*"):
scheduler.run_all_trials()
self.assertEqual(scheduler.run_trial_call_count, 3)
def test_failure_rate(self):
class SchedulerWithFrequentFailedTrials(TestScheduler):
poll_failed_next_time = True
def poll_trial_status(self) -> Dict[TrialStatus, Set[int]]:
running = [t.index for t in self.running_trials]
status = (
TrialStatus.FAILED
if self.poll_failed_next_time
else TrialStatus.COMPLETED
)
# Poll different status next time.
self.poll_failed_next_time = not self.poll_failed_next_time
return {status: {running[randint(0, len(running) - 1)]}}
class SchedulerWithAllFailedTrials(TestScheduler):
def poll_trial_status(self) -> Dict[TrialStatus, Set[int]]:
running = [t.index for t in self.running_trials]
return {TrialStatus.FAILED: {running[randint(0, len(running) - 1)]}}
options = SchedulerOptions(
total_trials=8,
tolerated_trial_failure_rate=0.5,
init_seconds_between_polls=0, # No wait between polls so test is fast.
min_failed_trials_for_failure_rate_check=2,
)
scheduler = SchedulerWithFrequentFailedTrials(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GS_no_parallelism,
options=options,
)
with self.assertRaises(FailureRateExceededError):
scheduler.run_all_trials()
# Trials will have statuses: 0, 2 - FAILED, 1 - COMPLETED. Failure rate
# is 0.5, and so if 2 of the first 3 trials are failed, we can fail
# immediately.
self.assertEqual(len(scheduler.experiment.trials), 3)
# If all trials fail, we can be certain that the sweep will
# fail after only 2 trials.
num_preexisting_trials = len(scheduler.experiment.trials)
scheduler = SchedulerWithAllFailedTrials(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GS_no_parallelism,
options=options,
)
self.assertEqual(scheduler._num_preexisting_trials, num_preexisting_trials)
with self.assertRaises(FailureRateExceededError):
scheduler.run_all_trials()
self.assertEqual(len(scheduler.experiment.trials), num_preexisting_trials + 2)
def test_retries_nonretriable_error(self):
# Check that no retries will be performed for `ValueError`, since we
# exclude it from the retriable errors.
self.branin_experiment.runner = BrokenRunnerValueError()
scheduler = Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(total_trials=1),
)
# Should raise right away since ValueError is non-retriable.
with self.assertRaisesRegex(ValueError, ".* testing .*"):
scheduler.run_all_trials()
self.assertEqual(scheduler.run_trial_call_count, 1)
def test_timeout(self):
# `TestScheduler` has `run_trial` and `fetch_trial_data` logic, so runner &
# implemented metrics are not required.
scheduler = TestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
total_trials=8,
init_seconds_between_polls=0, # No wait between polls so test is fast.
),
)
scheduler.run_all_trials(timeout_hours=0) # Forcing optimization to time out.
self.assertEqual(len(scheduler.experiment.trials), 0)
self.assertIn("aborted", scheduler.experiment._properties["run_trials_success"])
def test_logging(self):
with NamedTemporaryFile() as temp_file:
BareBonesTestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
total_trials=1,
init_seconds_between_polls=0, # No wait bw polls so test is fast.
log_filepath=temp_file.name,
),
).run_all_trials()
self.assertGreater(os.stat(temp_file.name).st_size, 0)
self.assertIn("Running trials [0]", str(temp_file.readline()))
temp_file.close()
def test_set_ttl(self):
scheduler = TestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
total_trials=2,
ttl_seconds_for_trials=1,
init_seconds_between_polls=0, # No wait between polls so test is fast.
min_seconds_before_poll=0.0,
),
)
scheduler.run_all_trials()
self.assertTrue(
all(t.ttl_seconds == 1 for t in scheduler.experiment.trials.values())
)
def test_stop_trial(self):
# With runners & metrics, `BareBonesTestScheduler.run_all_trials` should run.
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0.1, # Short between polls so test is fast.
),
)
with patch.object(
scheduler.experiment.runner, "stop", return_value=None
) as mock_runner_stop:
scheduler.run_n_trials(max_trials=1)
scheduler.stop_trial_run(scheduler.experiment.trials[0])
mock_runner_stop.assert_called_once()
def test_timeout(self):
scheduler = Scheduler(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
total_trials=8,
init_seconds_between_polls=
0, # No wait between polls so test is fast.
),
)
scheduler.run_all_trials(
timeout_hours=0) # Forcing optimization to time out.
self.assertEqual(len(scheduler.experiment.trials), 0)
self.assertIn("aborted",
scheduler.experiment._properties["run_trials_success"])
def test_run_preattached_trials_only(self):
# assert that pre-attached trials run when max_trials = 0
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0.1, # Short between polls so test is fast.
),
)
trial = scheduler.experiment.new_trial()
trial.add_arm(Arm(parameters={"x1": 5, "x2": 5}))
scheduler.run_n_trials(max_trials=0)
self.assertEqual(len(scheduler.experiment.trials), 1)
self.assertTrue( # Make sure all trials got to complete.
all(t.completed_successfully for t in scheduler.experiment.trials.values())
)
def test_suppress_all_storage_errors(self, mock_save_exp, _):
init_test_engine_and_session_factory(force_init=True)
config = SQAConfig()
encoder = Encoder(config=config)
decoder = Decoder(config=config)
db_settings = DBSettings(encoder=encoder, decoder=decoder)
BareBonesTestScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0.1, # Short between polls so test is fast.
suppress_storage_errors_after_retries=True,
),
db_settings=db_settings,
)
self.assertEqual(mock_save_exp.call_count, 3)
def test_run_trials_and_yield_results(self):
total_trials = 3
scheduler = BareBonesTestScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(init_seconds_between_polls=0, ),
)
# `BaseBonesTestScheduler.poll_trial_status` is written to mark one
# trial as `COMPLETED` at a time, so we should be obtaining results
# as many times as `total_trials` and yielding from generator after
# obtaining each new result.
res_list = list(
scheduler.run_trials_and_yield_results(max_trials=total_trials))
self.assertEqual(len(res_list), total_trials)
self.assertIsInstance(res_list, list)
self.assertDictEqual(
res_list[0], {"trials_completed_so_far": set(range(total_trials))})
def test_logging_level(self):
# We don't have any warnings yet, so warning level of logging shouldn't yield
# any logs as of now.
with NamedTemporaryFile() as temp_file:
BareBonesTestScheduler(
experiment=self.branin_experiment,
generation_strategy=self.sobol_GPEI_GS,
options=SchedulerOptions(
total_trials=3,
init_seconds_between_polls=0, # No wait bw polls so test is fast.
log_filepath=temp_file.name,
logging_level=WARNING,
),
).run_all_trials()
# Ensure that the temp file remains empty
self.assertEqual(os.stat(temp_file.name).st_size, 0)
temp_file.close()
def test_base_report_results(self):
class NoReportResultsScheduler(Scheduler):
def poll_trial_status(self) -> Dict[TrialStatus, Set[int]]:
if randint(0, 3) > 0:
running = [t.index for t in self.running_trials]
return {
TrialStatus.COMPLETED: {running[randint(0, len(running) - 1)]}
}
return {}
scheduler = NoReportResultsScheduler(
experiment=self.branin_experiment, # Has runner and metrics.
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(
init_seconds_between_polls=0,
),
)
self.assertEqual(scheduler.run_n_trials(max_trials=3), OptimizationResult())
def test_retries(self):
# Check that retries will be performed for a retriable error.
class BrokenSchedulerRuntimeError(BareBonesTestScheduler):
run_trial_call_count = 0
def run_trial(self, trial: BaseTrial) -> Dict[str, Any]:
self.run_trial_call_count += 1
raise RuntimeError("Failing for testing purposes.")
scheduler = BrokenSchedulerRuntimeError(
experiment=self.branin_experiment,
generation_strategy=self.two_sobol_steps_GS,
options=SchedulerOptions(total_trials=1),
)
# Should raise after 3 retries.
with self.assertRaisesRegex(RuntimeError, ".* testing .*"):
scheduler.run_all_trials()
self.assertEqual(scheduler.run_trial_call_count, 3)
