class_docstr: Environment wrapper for Multigrid environments.
  
  Note: the main difference with vanilla GymWrapper is that reward_spec() is
  overridden and rewards are cast to np.arrays in step()
docstr: Resets the episode.
docstr_tok: ["Resets","the","episode","."]
code: def reset(self) -> dm_env.TimeStep:
      """Resets the episode."""
      self._reset_next_step = False
      observation = self.process_obs(self._environment.reset())
  
      # Reset the diagnostic information.
      self._last_info = None
      return dm_env.restart(observation)
  
imports: from typing import Any, Dict, List, Optional
  import warnings
  from acme import specs
  from acme import types
  from acme import wrappers
  from acme.multiagent import types
  from acme.wrappers import multiagent_dict_key_wrapper
  import dm_env
  import gym
  from gym import spaces
  import jax
  import numpy
  import tree
label_desc: Use image node_id 3 for calling the MultigridWrapper obj's underlying member method code with example usage: obj.reset() and returns: dm_env