def run_search():
searchers = (RandomSearcher(get_space,
space_sample_validation_fn=lambda s: True),
MCTSSearcher(get_space, max_node_space=10),
EvolutionSearcher(get_space, 5, 3, regularized=False))
for searcher in searchers:
for i in range(100):
space_sample = searcher.sample()
assert space_sample.all_assigned == True
print(searcher.__class__.__name__, i,
space_sample.params_summary())
searcher.update_result(space_sample, np.random.uniform(0.1, 0.9))
from deeptables.datasets import dsutils
from deeptables.models.hyper_dt import *
from deeptables.utils import consts
from hypernets.core.callbacks import SummaryCallback, FileStorageLoggingCallback
from hypernets.core.searcher import OptimizeDirection
from hypernets.core.trial import DiskTrialStore
from hypernets.searchers.evolution_searcher import EvolutionSearcher
homedir = f'{consts.PROJECT_NAME}_run_dt_{time.strftime("%Y%m%d%H%M%S")}'
disk_trial_store = DiskTrialStore(f'hotexamples_com/trial_store')
# searcher = MCTSSearcher(mini_dt_space, max_node_space=0,optimize_direction=OptimizeDirection.Maximize)
# searcher = RandomSearcher(mini_dt_space, optimize_direction=OptimizeDirection.Maximize)
searcher = EvolutionSearcher(mini_dt_space,
200,
100,
regularized=True,
candidates_size=30,
optimize_direction=OptimizeDirection.Maximize)
hdt = HyperDT(searcher,
callbacks=[
SummaryCallback(),
FileStorageLoggingCallback(searcher,
output_dir=f'hotexamples_com/hyn_logs')
],
reward_metric='AUC',
earlystopping_patience=1)
space = mini_dt_space()
assert space.combinations == 589824
space2 = default_dt_space()
def test_set_random_state(self):
from hypernets.core import set_random_state
set_random_state(9527)
searcher = EvolutionSearcher(
get_space,
5,
3,
regularized=False,
optimize_direction=OptimizeDirection.Maximize)
vectors = []
for i in range(1, 10):
vectors.append(searcher.sample().vectors)
assert vectors == [[98, 0, 0, 0.96], [9, 0, 0, 0.93], [60, 0, 1, 0.24],
[54, 0, 1, 0.7], [25, 0, 1, 0.73], [67, 1, 1, 0.43],
[57, 1, 1, 0.05], [49, 0, 0, 0.71],
[71, 1, 1, 0.49]]
set_random_state(None)
searcher = EvolutionSearcher(
get_space,
5,
3,
regularized=False,
optimize_direction=OptimizeDirection.Maximize)
vectors = []
for i in range(1, 10):
vectors.append(searcher.sample().vectors)
assert vectors != [[98, 0, 0, 0.96], [9, 0, 0, 0.93], [60, 0, 1, 0.24],
[54, 0, 1, 0.7], [25, 0, 1, 0.73], [67, 1, 1, 0.43],
[57, 1, 1, 0.05], [49, 0, 0, 0.71],
[71, 1, 1, 0.49]]
set_random_state(9527)
searcher = EvolutionSearcher(
get_space,
5,
3,
regularized=False,
optimize_direction=OptimizeDirection.Maximize)
vectors = []
for i in range(1, 10):
vectors.append(searcher.sample().vectors)
assert vectors == [[98, 0, 0, 0.96], [9, 0, 0, 0.93], [60, 0, 1, 0.24],
[54, 0, 1, 0.7], [25, 0, 1, 0.73], [67, 1, 1, 0.43],
[57, 1, 1, 0.05], [49, 0, 0, 0.71],
[71, 1, 1, 0.49]]
set_random_state(1)
searcher = EvolutionSearcher(
get_space,
5,
3,
regularized=False,
optimize_direction=OptimizeDirection.Maximize)
vectors = []
for i in range(1, 10):
vectors.append(searcher.sample().vectors)
assert vectors == [[38, 1, 0, 0.93], [10, 1, 1, 0.15],
[17, 1, 0, 0.39], [7, 1, 0, 0.85], [19, 0, 1, 0.44],
[29, 1, 0, 0.67], [88, 1, 1, 0.43], [95, 0, 0, 0.8],
[10, 1, 1, 0.09]]
set_random_state(None)