code: def _create_objective_network_and_loss_fn_sequence(
      self,
  ) -> List[Tuple[DummyNet, tf.compat.v1.losses.mean_squared_error]]:
      return [
          (
              DummyNet(self._observation_spec, weights, self._bias),
              tf.compat.v1.losses.mean_squared_error,
          )
          for weights in self._kernel_weights
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from typing import List, Tuple
  import numpy
  import tensorflow
  from tf_agents.bandits.agents import greedy_multi_objective_neural_agent
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.multi_objective import multi_objective_scalarizer
  from tf_agents.bandits.networks import global_and_arm_feature_network
  from tf_agents.bandits.networks import heteroscedastic_q_network
  from tf_agents.bandits.specs import utils
  from tf_agents.networks import network
  from tf_agents.policies import utils
  from tf_agents.specs import array_spec
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import common
label_desc: Use image node_id 2 for calling the MultiObjectiveAgentTest obj's underlying member method code with example usage: obj._create_objective_network_and_loss_fn_sequence() and returns: unknown