class_docstr: Uses cloudpickle to serialize contents (otherwise multiprocessing tries to use pickle).
  
  :param var: (Any) the variable you wish to wrap for pickling with cloudpickle.
class_docstr_tok: ["Uses","cloudpickle","to","serialize","contents","(","otherwise","multiprocessing","tries","to","use","pickle",")",".",":","param","var",":","(","Any",")","the","variable","you","wish","to","wrap","for","pickling","with","cloudpickle","."]
code: def __init__(self, var):
      self.var = var
  
imports: import multiprocessing
  from typing import Callable, List, Iterable, Any, Tuple, Dict, Optional
  import cloudpickle
  import matplotlib
  import numpy
  from maze.core.annotations import override
  from maze.core.env.action_conversion import ActionType
  from maze.core.env.maze_env import MazeEnv
  from maze.core.env.observation_conversion import ObservationType
  from maze.core.log_stats.log_stats import LogStatsLevel
  from maze.core.wrappers.log_stats_wrapper import LogStatsWrapper
  from maze.train.parallelization.vector_env.structured_vector_env import StructuredVectorEnv
  from maze.train.parallelization.vector_env.vector_env import VectorEnv
  from maze.train.parallelization.vector_env.vector_env_utils import disable_epoch_level_stats
  from maze.train.utils.train_utils import stack_numpy_dict_list, unstack_numpy_list_dict
label_desc: Use image node_id 1 to create a new CloudpickleWrapper object from inherited base classes: object with example: obj = CloudpickleWrapper(var)