hunk.code_window:             action_vector[i] = action_dict[i][_DUMMY_AGENT_ID]
           self.new_obs, self.cur_rewards, self.cur_dones, self.cur_infos = \
               self.vector_env.vector_step(action_vector)
       @override(BaseEnv)
       def try_reset(self, env_id: Optional[EnvID] = None) -> MultiAgentDict:
           from ray.rllib.env.base_env import _DUMMY_AGENT_ID
           assert env_id is None or isinstance(env_id, int)
  
hunk.labels: keep keep keep keep keep replace keep keep
hunk.after_edit:     def try_reset(self, env_id: Optional[EnvID] = None) -> MultiEnvDict:
  
hunk.file_path: rllib/env/vector_env.py
hunk.type: replace
file: :orphan:
  
  tune_cifar_pytorch_pbt_example
  ==============================
  
  .. literalinclude:: /../../python/ray/train/examples/tune_cifar_pytorch_pbt_example.py
  