code: def make_network_from_module(
      module: hk.Transformed, spec: specs.EnvironmentSpec
  ) -> networks.FeedForwardNetwork:
      """Creates a network with dummy init arguments using the specified module.
  
      Args:
        module: Module that expects one batch axis and one features axis for its
          inputs.
        spec: EnvironmentSpec shapes to derive dummy inputs.
  
      Returns:
        FeedForwardNetwork whose `init` method only takes a random key, and `apply`
        takes an observation and action and produces an output.
      """
      dummy_obs = utils.add_batch_dim(
          utils.zeros_like(spec.observations)
      )
      dummy_action = utils.add_batch_dim(utils.zeros_like(spec.actions))
      return networks.FeedForwardNetwork(
          lambda key: module.init(key, dummy_obs, dummy_action),
          module.apply,
      )
  
file_path: acme/acme/agents/jax/mbop/networks.py
imports: import dataclasses
  from typing import Any, Tuple
  from acme import specs
  from acme.jax import networks
  from acme.jax import utils
  import haiku
  import jax.numpy
  import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: make_network_from_module(module, spec) and returns: networks