np.random.seed(args.manualSeed)
torch.manual_seed(args.manualSeed)
if cfg.CUDA:
torch.cuda.manual_seed_all(args.manualSeed)
##########################################################################
output_dir = '../output/%s' % (cfg.CONFIG_NAME)
model_dir = os.path.join(output_dir, 'Model')
image_dir = os.path.join(output_dir, 'Image')
log_dir = os.path.join(output_dir, 'Log')
mkdir_p(model_dir)
mkdir_p(image_dir)
mkdir_p(log_dir)
logger = setup_logger(name=cfg.CONFIG_NAME, save_dir=log_dir)
torch.cuda.set_device(cfg.GPU_ID)
cudnn.benchmark = True
# Get data loader ##################################################
imsize = cfg.TREE.BASE_SIZE * (2**(cfg.TREE.BRANCH_NUM - 1))
batch_size = cfg.TRAIN.BATCH_SIZE
if cfg.TRAIN.TRANS == 'org':
image_transform = transforms.Compose([
transforms.Scale(int(imsize * 76 / 64)),
transforms.RandomCrop(imsize),
transforms.RandomHorizontalFlip()
])
else:
image_transform = transforms.Compose([
if args.data_dir != '':
cfg.DATA_DIR = args.data_dir
assert 'real' in cfg.CONFIG_NAME
output_dir = '../output/%s_%s' % \
(cfg.DATASET_NAME, cfg.CONFIG_NAME)
log_dir = output_dir + '/log'
mkdir_p(output_dir)
mkdir_p(output_dir + '/imgs')
mkdir_p(output_dir + '/models')
mkdir_p(log_dir)
logger = setup_logger(cfg.CONFIG_NAME, log_dir)
logger.info('Using config:')
logger.info(str(cfg))
if not cfg.TRAIN.FLAG:
args.manualSeed = 100
elif args.manualSeed is None:
args.manualSeed = 100
#args.manualSeed = random.randint(1, 10000)
logger.info("seed now is : ", str(args.manualSeed))
random.seed(args.manualSeed)
np.random.seed(args.manualSeed)
torch.manual_seed(args.manualSeed)
#if cfg.CUDA:
torch.cuda.manual_seed_all(args.manualSeed)
cfg.GPU_ID = args.gpu_id
if args.data_dir != '':
cfg.DATA_DIR = args.data_dir
output_dir = '../output/%s_%s' % \
(cfg.DATASET_NAME, cfg.CONFIG_NAME)
log_dir = output_dir + '/log'
mkdir_p(output_dir)
mkdir_p(output_dir+'/imgs')
mkdir_p(output_dir+'/models')
mkdir_p(log_dir)
#logger = setup_logger(cfg.CONFIG_NAME,log_dir)
logger = setup_logger(cfg.CONFIG_NAME,'')
logger.info('Using config:')
logger.info(cfg)
if not cfg.TRAIN.FLAG:
args.manualSeed = 100
elif args.manualSeed is None:
args.manualSeed = 100
#args.manualSeed = random.randint(1, 10000)
logger.info("seed now is : ",args.manualSeed)
random.seed(args.manualSeed)
np.random.seed(args.manualSeed)
torch.manual_seed(args.manualSeed)
if cfg.CUDA:
torch.cuda.manual_seed_all(args.manualSeed)