code: def call(
      self, observations, step_type=(), network_state=(), training=False
  ):
      return self._sequential(observations, network_state)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.distributions import utils
  from tf_agents.keras_layers import dynamic_unroll_layer
  from tf_agents.keras_layers import inner_reshape
  from tf_agents.networks import nest_map
  from tf_agents.networks import network
  from tf_agents.networks import sequential
  from tf_agents.policies import actor_policy
  from tf_agents.policies import policy_saver
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 2 for calling the ActorNetwork obj's underlying member method code with example usage: obj.call(observations, step_type, network_state, training) and returns: self