def run_exp_1(self):
np.random.seed(162)
search_alg, cost = self.set_basic_conf()
search_alg = ConcurrencyLimiter(search_alg, 1)
results_exp_1 = tune.run(
cost, num_samples=5, search_alg=search_alg, verbose=0)
self.log_dir = os.path.join(self.tmpdir, "warmStartTest.pkl")
search_alg.save(self.log_dir)
return results_exp_1
def run_part_from_scratch(self):
np.random.seed(162)
search_alg, cost = self.set_basic_conf()
search_alg = ConcurrencyLimiter(search_alg, 1)
results_exp_1 = tune.run(cost,
num_samples=5,
search_alg=search_alg,
verbose=0,
name=self.experiment_name,
local_dir=self.tmpdir)
checkpoint_path = os.path.join(self.tmpdir, "warmStartTest.pkl")
search_alg.save(checkpoint_path)
return results_exp_1, np.random.get_state(), checkpoint_path
