code: def wrap_actor_core(
      actor_core: actor_core_lib.ActorCore,
      observation_spec: specs.Array,
      num_stacked_observations: int = 1,
  ) -> actor_core_lib.ActorCore:
      """Wraps an actor core so that it performs observation stacking."""
  
      if num_stacked_observations <= 0:
          raise ValueError(
              "Number of stacked observations must be strictly positive."
              f" Received num_stacked_observations={num_stacked_observations}."
          )
  
      if num_stacked_observations == 1:
          # Return unwrapped core when a trivial stack size is requested.
          return actor_core
  
      obs_stacker = ObservationStacker(
          observation_spec=observation_spec,
          stack_size=num_stacked_observations,
      )
  
      def init(key: jax_types.PRNGKey) -> StackingActorState:
          return StackingActorState(
              actor_state=actor_core.init(key),
              stacker_state=obs_stacker.initial_state(),
          )
  
      def select_action(
          params: Params,
          observations: Observation,
          state: StackingActorState,
      ) -> Tuple[Action, StackingActorState]:
          stacked_observations, stacker_state = obs_stacker(
              observations, state.stacker_state
          )
  
          actions, actor_state = actor_core.select_action(
              params, stacked_observations, state.actor_state
          )
          new_state = StackingActorState(
              actor_state=actor_state, stacker_state=stacker_state
          )
  
          return actions, new_state
  
      def get_extras(
          state: StackingActorState,
      ) -> Mapping[str, jnp.ndarray]:
          return actor_core.get_extras(state.actor_state)
  
      return actor_core_lib.ActorCore(
          init=init, select_action=select_action, get_extras=get_extras
      )
  
imports: from typing import Any, Mapping, NamedTuple, Tuple
  from acme import specs
  from acme import types
  from acme.agents.jax import actor_core
  from acme.jax import networks
  from acme.jax import types
  from acme.jax import utils
  from acme.tf import utils
  import jax
  import jax.numpy
  import reverb
  import tensorflow
  import tree
label_desc: Use image node_id 3 for calling a global function with example usage: wrap_actor_core(actor_core, observation_spec, num_stacked_observations) and returns: actor_core_lib, actor_core, StackingActorState, actions,  new_state, actor_core