nargs='?',
default=True,
help='Use CUDNN.')
args_parser = parser.parse_args()
if args_parser.seed is not None:
random.seed(args_parser.seed)
torch.manual_seed(args_parser.seed)
cudnn.enabled = True
cudnn.benchmark = args_parser.cudnn
configer = Configer(args_parser=args_parser)
abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir'))
configer.update(['data', 'data_dir'], abs_data_dir)
if configer.get('gpu') is not None:
os.environ["CUDA_VISIBLE_DEVICES"] = ','.join(
str(gpu_id) for gpu_id in configer.get('gpu'))
if configer.get('network', 'bn_type') is None:
configer.update(['network', 'bn_type'], 'torchbn')
project_dir = os.path.dirname(os.path.realpath(__file__))
configer.add(['project_dir'], project_dir)
if configer.get('logging', 'log_to_file'):
log_file = configer.get('logging', 'log_file')
new_log_file = '{}_{}'.format(
log_file, time.strftime("%Y-%m-%d_%X", time.localtime()))
nargs='?',
default=True,
help='Use CUDNN.')
args_parser = parser.parse_args()
if args_parser.seed is not None:
random.seed(args_parser.seed)
torch.manual_seed(args_parser.seed)
cudnn.enabled = True
cudnn.benchmark = args_parser.cudnn
configer = Configer(args_parser=args_parser)
abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir'))
configer.update(['data', 'data_dir'], abs_data_dir)
if configer.get('gpu') is not None:
os.environ["CUDA_VISIBLE_DEVICES"] = ','.join(
str(gpu_id) for gpu_id in configer.get('gpu'))
if configer.get('network', 'norm_type') is None:
configer.update(['network', 'norm_type'], 'batchnorm')
if configer.get('phase') == 'train':
assert len(configer.get('gpu')) > 1 or 'sync' not in configer.get(
'network', 'norm_type')
project_dir = os.path.dirname(os.path.realpath(__file__))
configer.add(['project_dir'], project_dir)
type=str2bool,
nargs='?',
default=True,
help='Use CUDNN.')
args_parser = parser.parse_args()
if args_parser.seed is not None:
random.seed(args_parser.seed)
torch.manual_seed(args_parser.seed)
cudnn.enabled = True
cudnn.benchmark = args_parser.cudnn
configer = Configer(args_parser=args_parser)
abs_data_dir = os.path.expanduser(configer.get('data', 'data_dir'))
configer.update(['data', 'data_dir'], abs_data_dir)
if configer.get('gpu') is not None:
os.environ["CUDA_VISIBLE_DEVICES"] = ','.join(
str(gpu_id) for gpu_id in configer.get('gpu'))
project_dir = os.path.dirname(os.path.realpath(__file__))
configer.add(['project_dir'], project_dir)
if configer.get('logging', 'log_to_file'):
log_file = configer.get('logging', 'log_file')
new_log_file = '{}_{}'.format(
log_file, time.strftime("%Y-%m-%d_%X", time.localtime()))
configer.update(['logging', 'log_file'], new_log_file)
else:
configer.update(['logging', 'logfile_level'], None)
