code: def _create_arm_policy_and_observations(
      self,
  ) -> Tuple[
      greedy_multi_objective_policy.GreedyMultiObjectiveNeuralPolicy,
      Dict[Text, tf.Tensor],
  ]:
      obs_spec = bandit_spec_utils.create_per_arm_observation_spec(
          2, 3, 4
      )
      time_step_spec = ts.time_step_spec(obs_spec)
      action_spec = tensor_spec.BoundedTensorSpec((), tf.int32, 0, 3)
      objective_networks = [
          global_and_arm_feature_network.create_feed_forward_common_tower_network(
              obs_spec, (4, 3), (3, 4), (4, 2)
          )
          for _ in range(3)
      ]
      policy = greedy_multi_objective_policy.GreedyMultiObjectiveNeuralPolicy(
          time_step_spec,
          action_spec,
          self._scalarizer,
          objective_networks,
          accepts_per_arm_features=True,
          emit_policy_info=(
              policy_utilities.InfoFields.PREDICTED_REWARDS_MEAN,
              policy_utilities.InfoFields.MULTIOBJECTIVE_SCALARIZED_PREDICTED_REWARDS_MEAN,
          ),
      )
      action_feature = tf.cast(
          tf.reshape(tf.random.shuffle(tf.range(24)), shape=[2, 4, 3]),
          dtype=tf.float32,
      )
      observations = {
          bandit_spec_utils.GLOBAL_FEATURE_KEY: tf.constant(
              [[1, 2], [2, 1]], dtype=tf.float32
          ),
          bandit_spec_utils.PER_ARM_FEATURE_KEY: action_feature,
      }
      return policy, observations
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from typing import Dict, List, Text, Tuple
  import numpy
  import tensorflow
  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.policies import greedy_multi_objective_neural_policy
  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 time_step
  from tf_agents.typing import types
  from tf_agents.utils import test_utils
label_desc: Use image node_id 4 for calling the GreedyRewardPredictionPolicyTest obj's underlying member method code with example usage: obj._create_arm_policy_and_observations() and returns: policy,  observations