class_docstr: Vectorized Environment Wrapper for MB-MPO.
  
  Primary change is in the `vector_step` method, which calls the dynamics
  models for next_obs "calculation" (instead of the actual env). Also, the
  actual envs need to have two extra methods implemented: `reward(obs)` and
  (optionally) `done(obs)`. If `done` is not implemented, we will assume
  that episodes in the env do not terminate, ever.
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docstr: Override parent to store actual env obs for upcoming predictions.
docstr_tok: ["Override","parent","to","store","actual","env","obs","for","upcoming","predictions","."]
code: def reset_at(self, index, *, seed=None, options=None):
      """Override parent to store actual env obs for upcoming predictions."""
      obs, infos = self.envs[index].reset(seed=seed, options=options)
      self.cur_obs[index] = obs
      self._timesteps[index] = 0
      return obs, infos
  
file_path: ray/rllib/env/wrappers/model_vector_env.py
imports: import logging
  from gymnasium.spaces import Discrete
  import numpy
  from ray.rllib.utils.annotations import override
  from ray.rllib.env.vector_env import VectorEnv
  from ray.rllib.evaluation.rollout_worker import get_global_worker
  from ray.rllib.env.base_env import BaseEnv, convert_to_base_env
  from ray.rllib.utils.typing import EnvType
label_desc: Use image node_id 3 for calling the _VectorizedModelGymEnv obj's underlying member method code with example usage: obj.reset_at(index) and returns: obs,  infos