def test_race_challenger_3(self):
'''
test _race_challenger with adaptive capping on a previously capped configuration
'''
def target(config: Configuration, seed: int, instance: str):
if instance == 1:
time.sleep(2.1)
else:
time.sleep(0.6)
return (config['a'] + 1) / 1000.
taf = ExecuteTAFuncDict(ta=target, stats=self.stats, run_obj="runtime", par_factor=1)
taf.runhistory = self.rh
intensifier = Intensifier(
tae_runner=taf, stats=self.stats,
traj_logger=TrajLogger(output_dir=None, stats=self.stats),
rng=np.random.RandomState(12345),
cutoff=2,
instances=[1])
self.rh.add(config=self.config1, cost=0.5, time=.5,
status=StatusType.SUCCESS, instance_id=1,
seed=12345,
additional_info=None)
# config2 should have a timeout (due to adaptive capping)
# and config1 should still be the incumbent
inc = intensifier._race_challenger(challenger=self.config2,
incumbent=self.config1,
run_history=self.rh,
aggregate_func=average_cost)
# self.assertTrue(False)
self.assertEqual(inc, self.config1)
# further run for incumbent
self.rh.add(config=self.config1, cost=2, time=2,
status=StatusType.TIMEOUT, instance_id=2,
seed=12345,
additional_info=None)
# give config2 a second chance
inc = intensifier._race_challenger(challenger=self.config2,
incumbent=self.config1,
run_history=self.rh,
aggregate_func=average_cost)
# the incumbent should still be config1 because
# config2 should get on inst 1 a full timeout
# such that c(config1) = 1.25 and c(config2) close to 1.3
self.assertEqual(inc, self.config1)
# the capped run should not be counted in runs_perf_config
self.assertAlmostEqual(self.rh.runs_per_config[2], 2)
def test_race_challenger_2(self):
'''
test _race_challenger with adaptive capping
'''
def target(x):
time.sleep(1.5)
return (x['a'] + 1) / 1000.
taf = ExecuteTAFuncDict(ta=target, stats=self.stats, run_obj="runtime")
taf.runhistory = self.rh
intensifier = Intensifier(tae_runner=taf,
stats=self.stats,
traj_logger=TrajLogger(output_dir=None,
stats=self.stats),
rng=np.random.RandomState(12345),
instances=[1])
self.rh.add(config=self.config1,
cost=.001,
time=0.001,
status=StatusType.SUCCESS,
instance_id=1,
seed=12345,
additional_info=None)
# config2 should have a timeout (due to adaptive capping)
# and config1 should still be the incumbent
inc = intensifier._race_challenger(challenger=self.config2,
incumbent=self.config1,
run_history=self.rh,
aggregate_func=average_cost)
# self.assertTrue(False)
self.assertEqual(inc, self.config1)
def test_race_challenger(self):
'''
test _race_challenger without adaptive capping
'''
def target(x):
return (x['a'] + 1) / 1000.
taf = ExecuteTAFuncDict(ta=target, stats=self.stats)
taf.runhistory = self.rh
intensifier = Intensifier(tae_runner=taf,
stats=self.stats,
traj_logger=TrajLogger(output_dir=None,
stats=self.stats),
rng=np.random.RandomState(12345),
instances=[1])
self.rh.add(config=self.config1,
cost=1,
time=1,
status=StatusType.SUCCESS,
instance_id=1,
seed=None,
additional_info=None)
inc = intensifier._race_challenger(challenger=self.config2,
incumbent=self.config1,
run_history=self.rh,
aggregate_func=average_cost)
self.assertEqual(inc, self.config2)
def test_race_challenger_large_blocked_seed(self):
"""
test _race_challenger whether seeds are blocked for challenger runs
"""
def target(x):
return 1
taf = ExecuteTAFuncDict(ta=target, stats=self.stats)
taf.runhistory = self.rh
intensifier = Intensifier(tae_runner=taf,
stats=self.stats,
traj_logger=TrajLogger(output_dir=None,
stats=self.stats),
rng=np.random.RandomState(12345),
instances=list(range(10)),
run_obj_time=False,
deterministic=False)
for i in range(10):
self.rh.add(config=self.config1,
cost=i + 1,
time=1,
status=StatusType.SUCCESS,
instance_id=i,
seed=i,
additional_info=None)
intensifier.stage = IntensifierStage.RUN_CHALLENGER
# tie on first instances and then challenger should always win
# and be returned as inc
while True:
config, _ = intensifier.get_next_challenger(
challengers=[self.config2, self.config3], chooser=None)
inc = intensifier._race_challenger(
challenger=config,
incumbent=self.config1,
run_history=self.rh,
)
# stop when challenger evaluation is over
if not intensifier.stage == IntensifierStage.RUN_CHALLENGER:
break
self.assertEqual(inc, self.config2)
self.assertEqual(self.rh.get_cost(self.config2), 1)
# get data for config2 to check that the correct run was performed
runs = self.rh.get_runs_for_config(self.config2,
only_max_observed_budget=True)
self.assertEqual(len(runs), 10)
seeds = sorted([r.seed for r in runs])
self.assertEqual(seeds, list(range(10)), seeds)
self.assertEqual(intensifier.num_run, 10)
self.assertEqual(intensifier.num_chall_run, 10)
def test_race_challenger_large_blocked_seed(self):
'''
test _race_challenger whether seeds are blocked for challenger runs
'''
def target(x):
return 1
taf = ExecuteTAFuncDict(ta=target, stats=self.stats)
taf.runhistory = self.rh
intensifier = Intensifier(tae_runner=taf,
stats=self.stats,
traj_logger=TrajLogger(output_dir=None,
stats=self.stats),
rng=np.random.RandomState(12345),
instances=list(range(10)),
deterministic=False)
for i in range(10):
self.rh.add(config=self.config1,
cost=i + 1,
time=1,
status=StatusType.SUCCESS,
instance_id=i,
seed=i,
additional_info=None)
# tie on first instances and then challenger should always win
# and be returned as inc
inc = intensifier._race_challenger(challenger=self.config2,
incumbent=self.config1,
run_history=self.rh,
aggregate_func=average_cost)
# self.assertTrue(False)
self.assertEqual(inc, self.config2)
self.assertEqual(self.rh.get_cost(self.config2), 1,
self.rh.get_cost(self.config2))
# get data for config2 to check that the correct run was performed
runs = self.rh.get_runs_for_config(self.config2)
self.assertEqual(len(runs), 10)
seeds = sorted([r.seed for r in runs])
self.assertEqual(seeds, list(range(10)), seeds)
