counter = mp.Value('i', 0)
steps = mp.Value('i', 0)
lock = mp.Lock()
torch.set_num_threads(1)
torch.manual_seed(args.seed)
env = create_vizdoom_env(args.config_path, args.train_scenario_path)
shared_model = ActorCritic(env.observation_space.spaces[0].shape[0],
env.action_space, args.topology)
shared_model.share_memory()
if args.no_shared:
optimizer = Adam(shared_model.parameters(), lr=args.lr)
else:
optimizer = SharedAdam(shared_model.parameters(), lr=args.lr)
optimizer.share_memory()
if args.checkpoint_path and os.path.isfile(args.checkpoint_path):
checkpoint = torch.load(args.checkpoint_path)
counter.value = checkpoint['episodes']
shared_model.load_state_dict(checkpoint['model'])
shared_model.share_memory()
optimizer.load_state_dict(checkpoint['optimizer'])
optimizer.share_memory()
else:
checkpoint = {}
processes = []
logging = build_logger(
lambda: dict(episodes=counter.value,
