parser.add_argument('--seed', type=int, default=1, metavar='S', help='random seed (default: 1)') parser.add_argument('--eval', type=bool, default=False, help='evaluate the model') parser.add_argument('--num_points', type=int, default=1024, help='num of points to use') parser.add_argument('--dropout', type=float, default=0.5, help='dropout rate') parser.add_argument('--model_path', type=str, default='', metavar='N', help='Pretrained model path') args = parser.parse_args() _init_(args) io = Logger('checkpoints/' + args.exp_name + '/run.log') 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: train(args, io) else: test(args, io)