code: def make_behavior_policy(
      networks: r2d2_networks.R2D2Networks,
      config: r2d2_config.R2D2Config,
      evaluation: bool = False,
  ) -> EpsilonRecurrentPolicy:
      """Selects action according to the policy."""
  
      def behavior_policy(
          params: networks_lib.Params,
          key: networks_lib.PRNGKey,
          observation: types.NestedArray,
          core_state: types.NestedArray,
          epsilon: float,
      ):
          q_values, core_state = networks.apply(
              params, key, observation, core_state
          )
          epsilon = config.evaluation_epsilon if evaluation else epsilon
          return (
              rlax.epsilon_greedy(epsilon).sample(key, q_values),
              core_state,
          )
  
      return behavior_policy
  
file_path: acme/acme/agents/jax/r2d2/actor.py
imports: from typing import Callable, Generic, Mapping, Optional, Tuple
  from acme import types
  from acme.agents.jax import actor_core
  from acme.agents.jax.r2d2 import config
  from acme.agents.jax.r2d2 import networks
  from acme.jax import networks
  import chex
  import jax
  import jax.numpy
  import numpy
  import rlax
label_desc: Use image node_id 2 for calling a global function with example usage: make_behavior_policy(networks, config, evaluation) and returns: behavior_policy, rlax,  core_state