code: def unstack_actions(
      batched_actions: types.NestedArray,
  ) -> types.NestedArray:
      """Returns a list of actions from potentially nested batch of actions."""
      flattened_actions = tf.nest.flatten(batched_actions)
      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
  from multiprocessing import dummy
  from multiprocessing import pool
  from typing import Sequence, Optional
  import gin
  import tensorflow
  from tf_agents.environments import py_environment
  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 1 for calling a global function with example usage: unstack_actions(batched_actions) and returns: unstacked_actions