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)