wenzhangliu
commented
12 months ago 你好，看到了你的问题描述，应该是在文件 "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_env.py" 第123行执行self.max_episode_length = self.env._max_episode_steps时出错， 很有可能是gym[atari]的版本不一样导致，请查看一下xuance/setup.py文件中关于各Python包的版本号，建议按照对应的版本号安装。
感谢您的使用，如有其他问题，欢迎随时联系。
玄策官方
------------------ 原始邮件 ------------------ 发件人: "agi-brain/xuance" @.>; 发送时间: 2023年11月22日(星期三) 晚上10:45 @.>; @.***>; 主题: [agi-brain/xuance] AttributeError: accessing private attribute '_max_episode_steps' is prohibited (Issue #12)
您好，这是版本不兼容的问题吗？
A.L.E: Arcade Learning Environment (version 0.8.1+53f58b7) [Powered by Stella] D:\Anaconda\envs\pycarla\lib\site-packages\gym\utils\passive_env_checker.py:32: UserWarning: WARN: A Box observation space has an unconventional shape (neither an image, nor a 1D vector). We recommend flattening the observation to have only a 1D vector or use a custom policy to properly process the data. Actual observation shape: (210, 160) "A Box observation space has an unconventional shape (neither an image, nor a 1D vector). " Traceback (most recent call last): File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\test.py", line 7, in is_test=False) File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\common\common_tools.py", line 166, in get_runner runner = run_REGISTRYargs[0].runner if type(args) == list else run_REGISTRYargs.runner File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\torch\runners\runner_drl.py", line 21, in init super(Runner_DRL, self).init(self.args) File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\torch\runners\runner_basic.py", line 11, in init self.envs = make_envs(args) File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environmentinit.py", line 68, in make_envs return REGISTRY_VECENV[config.vectorize]([thunk for in range(config.parallels)]) File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_vec_env.py", line 233, in init super(DummyVecEnv_Atari, self).init(env_fns) File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_vec_env.py", line 158, in init self.envs = [fn() for fn in env_fns] File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_vec_env.py", line 158, in self.envs = [fn() for fn in env_fns] File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment_init.py", line 58, in _thunk config.obs_type, config.frame_skip, config.num_stack, config.img_size, config.noop_max) File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_env.py", line 123, in init self.max_episode_length = self.env._max_episode_steps File "D:\Anaconda\envs\pycarla\lib\site-packages\gym\core.py", line 240, in getattr raise AttributeError(f"accessing private attribute '{name}' is prohibited") AttributeError: accessing private attribute '_max_episode_steps' is prohibited
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seuteer
您好，这是版本不兼容的问题吗？
A.L.E: Arcade Learning Environment (version 0.8.1+53f58b7) [Powered by Stella] D:\Anaconda\envs\pycarla\lib\site-packages\gym\utils\passive_env_checker.py:32: UserWarning: WARN: A Box observation space has an unconventional shape (neither an image, nor a 1D vector). We recommend flattening the observation to have only a 1D vector or use a custom policy to properly process the data. Actual observation shape: (210, 160) "A Box observation space has an unconventional shape (neither an image, nor a 1D vector). " Traceback (most recent call last): File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\test.py", line 7, in
is_test=False)
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\common\common_tools.py", line 166, in get_runner
runner = run_REGISTRYargs[0].runner if type(args) == list else run_REGISTRYargs.runner
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\torch\runners\runner_drl.py", line 21, in init
super(Runner_DRL, self).init(self.args)
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\torch\runners\runner_basic.py", line 11, in init
self.envs = make_envs(args)
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment__init.py", line 68, in make_envs
return REGISTRY_VEC_ENV[config.vectorize]([thunk for in range(config.parallels)])
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_vec_env.py", line 233, in init
super(DummyVecEnv_Atari, self).init(env_fns)
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_vec_env.py", line 158, in init
self.envs = [fn() for fn in env_fns]
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_vec_env.py", line 158, in
self.envs = [fn() for fn in env_fns]
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment__init__.py", line 58, in _thunk
config.obs_type, config.frame_skip, config.num_stack, config.img_size, config.noop_max)
File "D:\CODE\TrafficBigData\ReinforcementLearning\xuance-master\xuance\environment\gym\gym_env.py", line 123, in init__
self.max_episode_length = self.env._max_episode_steps
File "D:\Anaconda\envs\pycarla\lib\site-packages\gym\core.py", line 240, in getattr
raise AttributeError(f"accessing private attribute '{name}' is prohibited")
AttributeError: accessing private attribute '_max_episode_steps' is prohibited