code: def observe(
      self,
      obs: MultiAgentDict,
      rewards: MultiAgentDict,
      terminateds: MultiAgentDict,
      truncateds: MultiAgentDict,
      infos: MultiAgentDict,
  ):
      self.last_obs = obs
      for ag, r in rewards.items():
          if ag in self.last_rewards:
              self.last_rewards[ag] += r
          else:
              self.last_rewards[ag] = r
      for ag, d in terminateds.items():
          if ag in self.last_terminateds:
              self.last_terminateds[ag] = self.last_terminateds[ag] or d
          else:
              self.last_terminateds[ag] = d
      for ag, t in truncateds.items():
          if ag in self.last_truncateds:
              self.last_truncateds[ag] = self.last_truncateds[ag] or t
          else:
              self.last_truncateds[ag] = t
      self.last_infos = infos
  
imports: import gymnasium
  import logging
  from typing import Callable, Dict, List, Tuple, Optional, Union, Set, Type
  from ray.rllib.env.base_env import BaseEnv
  from ray.rllib.env.env_context import EnvContext
  from ray.rllib.utils.annotations import ExperimentalAPI, override, PublicAPI, DeveloperAPI
  from ray.rllib.utils.typing import AgentID, EnvCreator, EnvID, EnvType, MultiAgentDict, MultiEnvDict
  from ray.util import log_once
label_desc: Use image node_id 3 for calling the _MultiAgentEnvState obj's underlying member method code with example usage: obj.observe(obs, rewards, terminateds, truncateds, infos) without return types