code: def step(self, action):
      reward = self.rng.binomial(1, self._arm_probs[action])
      return [1.0], reward, True, False, {}
  
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 3 for calling the NonContextualBanditEnv obj's underlying member method code with example usage: obj.step(action) and returns: list,  reward,  True,  False,  dict