class_docstr: Base class for vectorized environments. Runs multiple independent copies of the same environment in parallel.
  
  This is not the same as 1 environment that has multiple subcomponents, but it is many copies of the same base env.
  
  Each observation returned from vectorized environment is a batch of observations for each parallel environment.
  And :meth:`step` is also expected to receive a batch of actions for each parallel environment.
  
  Notes:
      All parallel environments should share the identical observation and action spaces.
      In other words, a vector of multiple different environments is not supported.
docstr: Retrieves the results of a :meth:`reset_async` call.
  
  A call to this method must always be preceded by a call to :meth:`reset_async`.
  
  Args:
      seed: The reset seed
      options: Reset options
  
  Returns:
      The results from :meth:`reset_async`
  
  Raises:
      NotImplementedError: VectorEnv does not implement function
code: def reset_wait(
      self,
      seed: Optional[Union[int, List[int]]] = None,
      options: Optional[dict] = None,
  ):
      """Retrieves the results of a :meth:`reset_async` call.
  
      A call to this method must always be preceded by a call to :meth:`reset_async`.
  
      Args:
          seed: The reset seed
          options: Reset options
  
      Returns:
          The results from :meth:`reset_async`
  
      Raises:
          NotImplementedError: VectorEnv does not implement function
      """
      raise NotImplementedError("VectorEnv does not implement function")
  
imports: from typing import Any, List, Optional, Tuple, Union
  import numpy
  import gym
  from gym.vector.utils.spaces import batch_space
label_desc: Use image node_id 3 for calling the VectorEnv obj's underlying member method code with example usage: obj.reset_wait(seed, options) without return types