CODEWITHSUNDEEP
pythonmachine-learningartificial-intelligencereinforcement-learningstable-baselines
Andrew Jaramillo
Andrew Jaramillo

Reputation: 51

stable_baselines module error -> 'gym.logger' has no attribute 'MIN_LEVEL'

I am trying to use stable_baselines, but any model I try to use gives me the same error:

module 'gym.logger' has no attribute 'MIN_LEVEL'

I have attached an example from their website that is giving me the same error. I tried looking online but haven't had any success. Also, I am currently using Conda to create my environment with the following settings.

Tensorflow: 1.15.0 Python: 3.7.11

code bellow.

import gym

from stable_baselines.common.policies import MlpPolicy
from stable_baselines.common import make_vec_env
from stable_baselines import PPO2

# multiprocess environment
env = make_vec_env('CartPole-v1', n_envs=4)

model = PPO2(MlpPolicy, env, verbose=1)
model.learn(total_timesteps=25000)
model.save("ppo2_cartpole")

del model # remove to demonstrate saving and loading

model = PPO2.load("ppo2_cartpole")

# Enjoy trained agent
obs = env.reset()
while True:
    action, _states = model.predict(obs)
    obs, rewards, dones, info = env.step(action)
    env.render()

Full error:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/2l/c0wfhk2x0qz3v_6x0ylvvdr00000gn/T/ipykernel_4323/1825670659.py in <module>
      8 env = make_vec_env('CartPole-v1', n_envs=4)
      9 
---> 10 model = PPO2(MlpPolicy, env, verbose=1)
     11 model.learn(total_timesteps=25000)
     12 model.save("ppo2_cartpole")

~/miniconda3/envs/tf15/lib/python3.7/site-packages/stable_baselines/ppo2/ppo2.py in __init__(self, policy, env, gamma, n_steps, ent_coef, learning_rate, vf_coef, max_grad_norm, lam, nminibatches, noptepochs, cliprange, cliprange_vf, verbose, tensorboard_log, _init_setup_model, policy_kwargs, full_tensorboard_log, seed, n_cpu_tf_sess)
     95 
     96         if _init_setup_model:
---> 97             self.setup_model()
     98 
     99     def _make_runner(self):

~/miniconda3/envs/tf15/lib/python3.7/site-packages/stable_baselines/ppo2/ppo2.py in setup_model(self)
    108 
    109     def setup_model(self):
--> 110         with SetVerbosity(self.verbose):
    111 
    112             assert issubclass(self.policy, ActorCriticPolicy), "Error: the input policy for the PPO2 model must be " \

~/miniconda3/envs/tf15/lib/python3.7/site-packages/stable_baselines/common/base_class.py in __enter__(self)
   1127         self.tf_level = os.environ.get('TF_CPP_MIN_LOG_LEVEL', '0')
   1128         self.log_level = logger.get_level()
-> 1129         self.gym_level = gym.logger.MIN_LEVEL
   1130 
   1131         if self.verbose <= 1:

AttributeError: module 'gym.logger' has no attribute 'MIN_LEVEL'

Upvotes: 5

Views: 4772

Answers (5)

ali alsadadi
ali alsadadi

Reputation: 17

If you're on a Juypter notebook environment. try restarting the kernel. it worked for me.

Upvotes: -1

William
William

Reputation: 4028

I sloved this by go to :

Anaconda3\Lib\site-packages\stable_baselines\common\base_class.py

change :

self.gym_level = gym.logger.MIN_LEVEL

into :

self.gym_level = gym.logger

Upvotes: 2

Georg Grab
Georg Grab

Reputation: 2301

stable_baselines does not seem to fully work with the latest gym anymore, try installing a version of gym from around 2020:

pip install "gym==0.19.0"

That said, you should try to migrate to current stable_baselines3.

Upvotes: 2

Ying-Chuan Ni
Ying-Chuan Ni

Reputation: 11

I encountered the same problem. I manually changed all the "min_level"s in the gym.logger.py into "MIN_LEVEL"s. Or you can also change the "MIN_LEVEL" in stable_baselines.common.base_class.py into "min_level".

I guess this is an inconsistency between the new version of openai gym and stable baselines. (Using stable baselines 3 would not encounter this issue.)

Upvotes: 1

Masoud
Masoud

Reputation: 1351

You must update your gym module to the latest version with:

pip install gym[all] -U

in your command line

Upvotes: 0

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