code: def step(self, action):
      rewards = [[0, 3], [1, 2]]
  
      assert self.action_space.contains(action)
  
      if self.firstAction is None:
          self.firstAction = action
          reward = 0
          done = False
      else:
          reward = rewards[self.firstAction][action]
          done = True
  
      return self.get_obs(), reward, done, {}
  
file_path: keras-rl/utils/gym/envs/twoRoundDeterministicRewardEnv.py
imports: import gym
  from ..spaces import Discrete
label_desc: Use image node_id 2 for calling the TwoRoundDeterministicRewardEnv obj's underlying member method code with example usage: obj.step(action) and returns: self,  reward,  done,  dict