class_docstr: Env in which the initial observation has to be repeated all the time.
  
  Runs for n steps.
  r=1 if action correct, -1 otherwise (max. R=100).
code: def __init__(self, episode_len=100):
      self.observation_space = Discrete(2)
      self.action_space = Discrete(2)
      self.token = None
      self.episode_len = episode_len
      self.num_steps = 0
  
file_path: ray/python/ray/rllib/examples/env/repeat_initial_obs_env.py
imports: import gymnasium
  from gymnasium.spaces import Discrete
  import random
label_desc: Use image node_id 1 to create a new RepeatInitialObsEnv object from inherited base classes: gym with example: obj = RepeatInitialObsEnv(episode_len)