code: def get_default_eval_policy(
      networks: D4PGNetworks,
  ) -> actor_core_lib.FeedForwardPolicy:
      """Selects action according to the training policy."""
  
      def behavior_policy(
          params: networks_lib.Params,
          key: networks_lib.PRNGKey,
          observation: types.NestedArray,
      ):
          del key
          action = networks.policy_network.apply(params, observation)
          return action
  
      return behavior_policy
  
file_path: acme/acme/agents/jax/d4pg/networks.py
imports: import dataclasses
  from typing import Sequence
  from acme import specs
  from acme import types
  from acme.agents.jax import actor_core
  from acme.agents.jax.d4pg import config
  from acme.jax import networks
  from acme.jax import utils
  import haiku
  import jax.numpy
  import numpy
  import rlax
label_desc: Use image node_id 2 for calling a global function with example usage: get_default_eval_policy(networks) and returns: behavior_policy, action