parser.add_argument("--title",
type=str,
help="experiment title",
required=True)
args = parser.parse_args()
CONFIG = get_config(args.cfg)
if CONFIG.cuda:
device = torch.device("cuda" if (
torch.cuda.is_available() and CONFIG.ngpu > 0) else "cpu")
else:
device = torch.device("cpu")
get_logger(CONFIG.log_dir)
writer = get_writer(args.title, CONFIG.write_dir)
logging.info(
"=================================== Experiment title : {} Start ==========================="
.format(args.title))
set_random_seed(CONFIG.seed)
train_transform, val_transform, test_transform = get_transforms(CONFIG)
train_dataset, val_dataset, test_dataset = get_dataset(
train_transform, val_transform, test_transform, CONFIG)
train_loader, val_loader, test_loader = get_dataloader(
train_dataset, val_dataset, test_dataset, CONFIG)
generator = get_generator(CONFIG, 21 * 8)
parser.add_argument("--evaluate-arch-param", action="store_true", default=False, help="whether to evaluate arch_param")
parser.add_argument("--evaluate-lookup_table", action="store_true", default=False, help="whether to evaluate lookup_table")
parser.add_argument("--loading-architectures", action="store_true", default=False, help="whether to load the architecture")
parser.add_argument("--generate-architecture-parameter", action="store_true", default=False, help="generate architecture")
parser.add_argument("--target-macs", type=int, help="target macs")
args = parser.parse_args()
CONFIG = get_config(args.cfg)
if CONFIG.cuda:
device = torch.device("cuda" if (torch.cuda.is_available() and CONFIG.ngpu > 0) else "cpu")
else:
device = torch.device("cpu")
get_logger(CONFIG.log_dir)
writer = get_writer(CONFIG.write_dir)
#set_random_seed(CONFIG.seed)
train_transform, val_transform, test_transform = get_transforms(CONFIG)
train_dataset, val_dataset, test_dataset = get_dataset(train_transform, val_transform, test_transform, CONFIG)
train_loader, val_loader, test_loader = get_dataloader(train_dataset, val_dataset, test_dataset, CONFIG)
model = Supernet(CONFIG)
lookup_table = LookUpTable(CONFIG)
arch_param_nums = model.get_arch_param_nums()
#generator = ConvGenerator(CONFIG.hc_dim, 1, CONFIG.hidden_dim)
generator = get_generator(CONFIG, arch_param_nums)
criterion = cross_encropy_with_label_smoothing