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)