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__