code: def step(self, action_dict):
      obs, rew, terminated, truncated = {}, {}, {}, {}
      for i, action in action_dict.items():
          self.timesteps[i] += 1
          obs[i] = np.array(
              [i, action[0], action[1], self.timesteps[i]]
          )
          rew[i] = self.timesteps[i] % 3
          terminated[i] = False
          truncated[i] = (
              True
              if self.timesteps[i] > self.base_episode_len + i
              else False
          )
          if terminated[i]:
              self.terminateds.add(i)
          if truncated[i]:
              self.truncateds.add(i)
      terminated["__all__"] = len(self.terminateds) == self.num_agents
      truncated["__all__"] = len(self.truncateds) == self.num_agents
      return obs, rew, terminated, truncated, {}
  
file_path: ray/rllib/examples/env/debug_counter_env.py
imports: import gymnasium
  import numpy
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
label_desc: Use image node_id 3 for calling the MultiAgentDebugCounterEnv obj's underlying member method code with example usage: obj.step(action_dict) and returns: obs,  rew,  terminated,  truncated,  dict