parser.add_argument("--debug", action="store_true", dest="debug", help="log all the computation details") parser.add_argument("--no-debug", action="store_false", dest="debug", help="turn off debug logs") parser.set_defaults(debug=False) return parser.parse_args() if __name__ == '__main__': cmd_args = parse_args() common.set_house_IDs(cmd_args.env_set, ensure_kitchen=(not cmd_args.multi_target)) print('>> Environment Set = <%s>, Total %d Houses!' % (cmd_args.env_set, len(common.all_houseIDs))) common.ensure_object_targets(cmd_args.object_target) if cmd_args.seed is not None: np.random.seed(cmd_args.seed) random.seed(cmd_args.seed) torch.manual_seed(cmd_args.seed) #optional if cmd_args.action_dim is not None: print('Degree of freedom set to be <{}>!'.format(cmd_args.action_dim)) common.action_shape = (cmd_args.action_dim, 2) if cmd_args.linear_reward:
parser.add_argument("--rnn-layers", type=int, help="[RNN-Only] number of layers in RNN") parser.add_argument("--rnn-cell", choices=['lstm', 'gru'], help="[RNN-Only] RNN cell type") # Checkpointing parser.add_argument("--save-dir", type=str, default="./_graph_", help="directory in which graph parameters and logs will be stored") parser.add_argument("--warmstart", type=str, help="file to load a pre-trained graph") return parser.parse_args() if __name__ == '__main__': args = parse_args() assert (args.warmstart is None) or (os.path.exists(args.warmstart)), 'Graph File Not Exists!' assert (args.motion_warmstart is None) or (os.path.exists(args.motion_warmstart)), 'Policy Model File Not Exists!' common.set_house_IDs(args.env_set) print('>> Environment Set = <%s>, Total %d Houses!' % (args.env_set, len(common.all_houseIDs))) common.ensure_object_targets() if not os.path.exists(args.save_dir): print('Directory <{}> does not exist! Creating directory ...'.format(args.save_dir)) os.makedirs(args.save_dir) if args.motion not in ['fake', 'random']: assert args.motion_warmstart is not None if args.seed is None: args.seed = 0 dict_args = args.__dict__