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 reset(self, *, seed=None, options=None):
      self.token = random.choice([0, 1])
      self.num_steps = 0
      return self.token, {}
  
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 2 for calling the RepeatInitialObsEnv obj's underlying member method code with example usage: obj.reset() and returns: self,  dict