code: def get_fake_n_step_return() -> networks_lib.FeedForwardNetwork:
      def apply(params, observation_t, action_t):
          del params, action_t
          return jnp.ones((observation_t.shape[0], 1))
  
      return networks_lib.FeedForwardNetwork(
          init=lambda: None, apply=apply
      )
  
imports: import functools
  from typing import Any
  from acme import specs
  from acme.agents.jax.mbop import ensemble
  from acme.agents.jax.mbop import models
  from acme.agents.jax.mbop import mppi
  from acme.jax import networks
  import jax
  import jax.numpy
  import numpy
  from absl.testing import absltest
  from absl.testing import parameterized
label_desc: Use image node_id 3 for calling a global function with example usage: get_fake_n_step_return() and returns: networks_lib, jnp