def test_enough_time_to_train(self):
model_type = "Xgboost"
model_type_2 = "LightGBM"
model_type = "Xgboost"
automl = AutoML(
results_path=self.automl_dir,
total_time_limit=10,
model_time_limit=10,
algorithms=[model_type, model_type_2],
)
automl._time_ctrl = TimeController(
time.time(),
10,
10,
["simple_algorithms", "not_so_random"],
[model_type, model_type_2],
)
for i in range(5):
automl._time_ctrl.log_time(f"Xgboost_{i}", model_type,
"not_so_random", 1)
# should be always true
self.assertTrue(
automl._time_ctrl.enough_time(model_type, "not_so_random"))
for i in range(5):
automl._time_ctrl.log_time(f"LightGBM_{i}", model_type_2,
"not_so_random", 1)
# should be always true
self.assertTrue(
automl._time_ctrl.enough_time(model_type_2, "not_so_random"))
def test_set_model_time_limit(self):
model_type = "Xgboost"
automl = AutoML(results_path=self.automl_dir,
model_time_limit=10,
algorithms=[model_type])
automl._time_ctrl = TimeController(
time.time(), None, 10, ["simple_algorithms", "not_so_random"],
"Xgboost")
for i in range(12):
automl._time_ctrl.log_time(f"Xgboost_{i}", model_type,
"not_so_random", 10)
# should be always true
self.assertTrue(
automl._time_ctrl.enough_time(model_type, "not_so_random"))
def test_set_total_time_limit(self):
model_type = "Xgboost"
automl = AutoML(results_path=self.automl_dir,
total_time_limit=100,
algorithms=[model_type])
automl._time_ctrl = TimeController(
time.time(), 100, None, ["simple_algorithms", "not_so_random"],
"Xgboost")
time_spend = 0
for i in range(12):
automl._start_time -= 10
automl._time_ctrl.log_time(f"Xgboost_{i}", model_type,
"not_so_random", 10)
if automl._time_ctrl.enough_time(model_type, "not_so_random"):
time_spend += 10
self.assertTrue(time_spend < 100)