def test_single_train_iter(self):
single_train_iter(
self,
self.scenario,
debug=False,
args=AdditionalTrainerArgs(input_gradient_regularization=True,
preload_data=True),
)
def test_single_train_iter(self):
# single_train_iter(self, self.get_scenario_parallel(), debug=False)
import signal
t1 = time.time()
single_train_iter(self, self.get_scenario_none_parallel(), debug=False)
none_paralle_time = time.time() - t1
import math
def handler(signum, frame):
print("Timeout reached!")
raise TimeoutError(
"Parallel inputpipeline took at least twice as long as the none parallel version. It's probably stuckt!"
)
print(
f"### Parallel input test timeout: {int(math.ceil(none_paralle_time * 2))} ######"
)
signal.signal(signal.SIGALRM, handler)
signal.alarm(int(math.ceil(none_paralle_time * 2)))
single_train_iter(self, self.get_scenario_parallel(), debug=False)
signal.alarm(0)
def test_single_train_iter(self):
single_train_iter(self,
self.get_scenario(),
debug=False,
lav_every_n=0)
def test_single_train_iter(self):
single_train_iter(self, self.get_scenario(), debug=False)
def test_single_train_iter_debug(self):
single_train_iter(self, TutorialScenarioTest, debug=True)
def test_single_train_iter(self):
single_train_iter(self, TutorialScenarioTest, debug=False)
def test_single_train_iter(self):
single_train_iter(
self,
TutorialScenarioTest,
debug=False,
args=AdditionalTrainerArgs(input_gradient_regularization=True))
def test_single_train_iter(self):
single_train_iter(self, TemplateScenario)