def state(): return BaseEnv('test_map').state
from examples.utils.utils import get_policy tensorboard_folder = './tensorboard/Bomberman/base/' model_folder = './models/Bomberman/base/' if not os.path.isdir(tensorboard_folder): os.makedirs(tensorboard_folder) if not os.path.isdir(model_folder): os.makedirs(model_folder) policy = '' model_tag = '' if len(sys.argv) > 1: policy = sys.argv[1] model_tag = '_' + sys.argv[1] env = DummyVecEnv([lambda: BaseEnv()]) env = VecFrameStack(env, 3) model = A2C(get_policy(policy), env, verbose=0, tensorboard_log=tensorboard_folder) model.learn(total_timesteps=2500000, tb_log_name='A2C' + model_tag) model.save(model_folder + "A2C" + model_tag) del model model = A2C.load(model_folder + "A2C" + model_tag) done = False states = None obs = env.reset()
def base_env(): return BaseEnv('test_map')