code: def __init__(self, config: EnvContext):
      best_arm_prob = config.get("best_arm_prob", 0.5)
      self.action_space = Discrete(2)
      self.observation_space = Box(
          0.0, 1.0, shape=(1,), dtype=np.float32
      )
      self.reset(seed=0)
      self._arm_probs = {0: 0.1, 1: best_arm_prob}
  
imports: import unittest
  import gymnasium
  import numpy
  from gymnasium.spaces import Box, Discrete
  from rllib_bandit.bandit.bandit import BanditLinTSConfig, BanditLinUCBConfig
  from rllib_bandit.env.bandit_envs_discrete import SimpleContextualBandit
  import ray
  from ray.rllib.env import EnvContext
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.test_utils import check, check_train_results, framework_iterator
label_desc: Use image node_id 1 to create a new NonContextualBanditEnv object from inherited base classes: gym with example: obj = NonContextualBanditEnv(config)