class_docstr: Batch together environments and simulate them in external processes.
  
  The environments are created in external processes by calling the provided
  callables. This can be an environment class, or a function creating the
  environment and potentially wrapping it. The returned environment should not
  access global variables.
class_docstr_tok: ["Batch","together","environments","and","simulate","them","in","external","processes",".","The","environments","are","created","in","external","processes","by","calling","the","provided","callables",".","This","can","be","an","environment","class",",","or","a","function","creating","the","environment","and","potentially","wrapping","it",".","The","returned","environment","should","not","access","global","variables","."]
docstr: Returns a list of actions from potentially nested batch of actions.
docstr_tok: ["Returns","a","list","of","actions","from","potentially","nested","batch","of","actions","."]
code: def _unstack_actions(self, batched_actions):
      """Returns a list of actions from potentially nested batch of actions."""
      flattened_actions = tf.nest.flatten(batched_actions)
      if self._flatten:
          unstacked_actions = zip(*flattened_actions)
      else:
          unstacked_actions = [
              tf.nest.pack_sequence_as(batched_actions, actions)
              for actions in zip(*flattened_actions)
          ]
      return unstacked_actions
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import atexit
  import sys
  import traceback
  from typing import Any, Callable, Sequence, Text, Union
  from absl import logging
  import cloudpickle
  import gin
  import numpy
  import tensorflow
  from tf_agents.environments import py_environment
  from tf_agents.system import system_multiprocessing
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 13 for calling the ParallelPyEnvironment obj's underlying member method code with example usage: obj._unstack_actions(batched_actions) and returns: unstacked_actions