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: Returns a string representation of the vector environment.
  
  Returns:
      A string containing the class name, number of environments and environment spec id
code: def __repr__(self) -> str:
      """Returns a string representation of the vector environment.
  
      Returns:
          A string containing the class name, number of environments and environment spec id
      """
      if self.spec is None:
          return f"{self.__class__.__name__}({self.num_envs})"
      else:
          return f"{self.__class__.__name__}({self.spec.id}, {self.num_envs})"
  
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 18 for calling the VectorEnv obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str, self, str, self, str