default=1024,
help='num of points to use')
parser.add_argument('--model_path',
type=str,
default='',
metavar='N',
help='Pretrained model path')
parser.add_argument('--trans_open',
type=bool,
default=True,
metavar='N',
help='enables input translation during voting')
args = parser.parse_args()
_init_()
io = IOStream('checkpoints/' + args.exp_name + '/%s_voting.log' %
(args.exp_name))
io.cprint(str(args))
args.cuda = not args.no_cuda and torch.cuda.is_available()
torch.manual_seed(args.seed)
if args.cuda:
io.cprint('Using GPU')
torch.cuda.manual_seed(args.seed)
else:
io.cprint('Using CPU')
test(args, io)
help='evaluate the model')
parser.add_argument('--num_points',
type=int,
default=1024,
help='num of points to use')
parser.add_argument('--model_path',
type=str,
default='',
metavar='N',
help='Pretrained model path')
args = parser.parse_args()
_init_()
if not args.eval:
io = IOStream('checkpoints/' + args.exp_name + '/%s_train.log' %
(args.exp_name))
else:
io = IOStream('checkpoints/' + args.exp_name + '/%s_test.log' %
(args.exp_name))
io.cprint(str(args))
args.cuda = not args.no_cuda and torch.cuda.is_available()
torch.manual_seed(args.seed)
if args.cuda:
io.cprint('Using GPU : ' + str(torch.cuda.current_device()) +
' from ' + str(torch.cuda.device_count()) + ' devices')
torch.cuda.manual_seed(args.seed)
else:
io.cprint('Using CPU')
if not args.eval: