class TestFCNetProteinStructure(unittest.TestCase):
def setUp(self):
self.b = FCNetProteinStructureBenchmark(
data_dir="./fcnet_tabular_benchmarks/")
def test_random_sampling(self):
config = self.b.get_configuration_space().sample_configuration()
self.b.objective_function(config)
b = FCNetNavalPropulsionBenchmark(data_dir=args.data_dir)
elif args.benchmark == "parkinsons_telemonitoring":
b = FCNetParkinsonsTelemonitoringBenchmark(data_dir=args.data_dir)
output_path = os.path.join(args.output_path, "random_search")
os.makedirs(os.path.join(output_path), exist_ok=True)
cs = b.get_configuration_space()
runtime = []
regret = []
curr_incumbent = None
curr_inc_value = None
rt = 0
X = []
for i in range(args.n_iters):
config = cs.sample_configuration()
b.objective_function(config)
if args.benchmark == "nas_cifar10a" or args.benchmark == "nas_cifar10b" or args.benchmark == "nas_cifar10c":
res = b.get_results(ignore_invalid_configs=True)
else:
res = b.get_results()
fh = open(os.path.join(output_path, 'run_%d.json' % args.run_id), 'w')
json.dump(res, fh)
fh.close()
from tabular_benchmarks import FCNetProteinStructureBenchmark
b = FCNetProteinStructureBenchmark(data_dir="./fcnet_tabular_benchmarks/")
cs = b.get_configuration_space()
config = cs.sample_configuration()
print("Numpy representation: ", config.get_array())
print("Dict representation: ", config.get_dictionary())
max_epochs = 100
y, cost = b.objective_function(config, budget=max_epochs)
print(y, cost)