def intensify(self,
challengers: typing.List[Configuration],
incumbent: Configuration,
run_history: RunHistory,
aggregate_func: typing.Callable,
time_bound: float = float(MAXINT),
log_traj: bool = True):
"""Running intensification to determine the incumbent configuration.
*Side effect:* adds runs to run_history
Implementation of Procedure 2 in Hutter et al. (2011).
Parameters
----------
challengers : typing.List[Configuration]
promising configurations
incumbent : Configuration
best configuration so far
run_history : RunHistory
stores all runs we ran so far
aggregate_func: typing.Callable
aggregate error across instances
time_bound : float, optional (default=2 ** 31 - 1)
time in [sec] available to perform intensify
log_traj: bool
whether to log changes of incumbents in trajectory
Returns
-------
incumbent: Configuration()
current (maybe new) incumbent configuration
inc_perf: float
empirical performance of incumbent configuration
"""
self.start_time = time.time()
self._ta_time = 0
if time_bound < self._min_time:
raise ValueError("time_bound must be >= %f" % (self._min_time))
self._num_run = 0
self._chall_indx = 0
# Line 1 + 2
if isinstance(challengers, ChallengerList):
challengers = challengers.challengers
L1 = 10
L2 = 10000
r = np.random.uniform()
if 0.05 < r < 0.2 and len(challengers) > L1:
target = np.random.randint(1, L1)
challengers[target], challengers[0] = challengers[0], challengers[
target]
if r < 0.05 and len(challengers) > L2:
target = np.random.randint(L1, L2)
challengers[target], challengers[0] = challengers[0], challengers[
target]
for challenger in challengers:
if not run_history.db.appointment_config(challenger):
continue
if challenger == incumbent:
self.logger.debug(
"Challenger was the same as the current incumbent; Skipping challenger"
)
continue
self.logger.debug("Intensify on %s", challenger)
if hasattr(challenger, 'origin'):
self.logger.debug("Configuration origin: %s",
challenger.origin)
try:
# Lines 3-7
self._add_inc_run(incumbent=incumbent, run_history=run_history)
# Lines 8-17
incumbent = self._race_challenger(
challenger=challenger,
incumbent=incumbent,
run_history=run_history,
aggregate_func=aggregate_func,
log_traj=log_traj)
if self.always_race_against and \
challenger == incumbent and \
self.always_race_against != challenger:
self.logger.debug(
"Race against constant configuration after incumbent change."
)
incumbent = self._race_challenger(
challenger=self.always_race_against,
incumbent=incumbent,
run_history=run_history,
aggregate_func=aggregate_func,
log_traj=log_traj)
except BudgetExhaustedException:
# We return incumbent, SMBO stops due to its own budget checks
inc_perf = run_history.get_cost(incumbent)
self.logger.debug("Budget exhausted; Return incumbent")
return incumbent, inc_perf
tm = time.time()
if self._chall_indx >= self.min_chall:
if self._num_run > self.run_limit:
self.logger.debug(
"Maximum #runs for intensification reached")
break
if not self.use_ta_time_bound and tm - self.start_time - time_bound >= 0:
self.logger.debug(
"Wallclock time limit for intensification reached ("
"used: %f sec, available: %f sec)" %
(tm - self.start_time, time_bound))
break
elif self._ta_time - time_bound >= 0:
self.logger.debug(
"TA time limit for intensification reached ("
"used: %f sec, available: %f sec)" %
(self._ta_time, time_bound))
break
# output estimated performance of incumbent
inc_runs = run_history.get_runs_for_config(incumbent)
inc_perf = aggregate_func(incumbent, run_history, inc_runs)
self.logger.info(
"Updated estimated cost of incumbent on %d runs: %.4f" %
(len(inc_runs), inc_perf))
self.stats.update_average_configs_per_intensify(
n_configs=self._chall_indx)
return incumbent, inc_perf
from dsmac.runhistory.runhistory import RunHistoryDB
from dsmac.runhistory.utils import get_id_of_config
from dsmac.tae.execute_ta_run import StatusType
if __name__ == '__main__':
from ConfigSpace import ConfigurationSpace
import joblib
from dsmac.optimizer.objective import average_cost
from dsmac.runhistory.runhistory import RunHistory
runhistory = RunHistory(average_cost,db_args="test.db")
cs: ConfigurationSpace = joblib.load("/home/tqc/PycharmProjects/auto-pipeline/test/php.bz2")
runhistory.load_json(
"/home/tqc/PycharmProjects/auto-pipeline/test/test_runhistory/default_dataset_name/smac_output/runhistory.json",
cs)
all_configs = (runhistory.get_all_configs())
config = all_configs[0]
config_id = get_id_of_config(config)
cost = runhistory.get_cost(config)
db = RunHistoryDB(cs, runhistory, "test.db")
db.delete_all()
ans = db.appointment_config(config)
print(ans)
db.insert_runhistory(config, cost, 0.1, StatusType.SUCCESS)
db2 = RunHistoryDB(cs, runhistory, "test.db")
db2.insert_runhistory(all_configs[1], runhistory.get_cost(all_configs[1]), 0.1, StatusType.SUCCESS)
db.fetch_new_runhistory()