code: def make_network(spec: specs.EnvironmentSpec) -> bc.BCNetworks:
      """Creates networks used by the agent."""
      num_actions = spec.actions.num_values
  
      def actor_fn(obs, is_training=True, key=None):
          # is_training and key allows to utilize train/test dependant modules
          # like dropout.
          del is_training
          del key
          mlp = hk.Sequential(
              [hk.Flatten(), hk.nets.MLP([64, 64, num_actions])]
          )
          return mlp(obs)
  
      policy = hk.without_apply_rng(hk.transform(actor_fn))
  
      # Create dummy observations to create network parameters.
      dummy_obs = utils.zeros_like(spec.observations)
      dummy_obs = utils.add_batch_dim(dummy_obs)
  
      policy_network = bc.BCPolicyNetwork(
          lambda key: policy.init(key, dummy_obs), policy.apply
      )
  
      def sample_fn(
          logits: networks_lib.NetworkOutput, key: jax_types.PRNGKey
      ) -> networks_lib.Action:
          return rlax.epsilon_greedy(epsilon=0.0).sample(key, logits)
  
      def log_prob(
          logits: networks_lib.Params, actions: networks_lib.Action
      ) -> networks_lib.LogProb:
          logits_actions = jnp.sum(
              jax.nn.one_hot(actions, logits.shape[-1]) * logits,
              axis=-1,
          )
          logits_actions = logits_actions - special.logsumexp(
              logits, axis=-1
          )
          return logits_actions
  
      return bc.BCNetworks(policy_network, sample_fn, log_prob)
  
imports: import functools
  import operator
  from typing import Callable
  from acme import core
  from acme import environment_loop
  from acme import specs
  from acme import types
  from acme.agents.jax import actor_core
  from acme.agents.jax import actors
  from acme.agents.jax import bc
  from acme.agents.tf.dqfd import bsuite_demonstrations
  from acme.jax import networks
  from acme.jax import types
  from acme.jax import utils
  from acme.jax import variable_utils
  from acme.jax.deprecated import offline_distributed_layout
  from acme.utils import counting
  from acme.utils import loggers
  from acme.wrappers import single_precision
  import bsuite
  import dm_env
  import haiku
  import jax
  import jax.numpy
  from jax.scipy import special
  import rlax
  import tensorflow
  import tree
label_desc: Use image node_id 1 for calling a global function with example usage: make_network(spec) and returns: bc, mlp, rlax, logits_actions