code: def testBanditPolicyType(self):
      policy = (
          falcon_reward_prediction_policy.FalconRewardPredictionPolicy(
              self._time_step_spec,
              self._action_spec,
              reward_network=DummyNet(self._obs_spec),
              emit_policy_info=(utils.InfoFields.BANDIT_POLICY_TYPE,),
          )
      )
      observations = tf.constant([[1, 2], [3, 4]], dtype=tf.float32)
      time_step = ts.restart(observations, batch_size=2)
      action_step = policy.action(time_step, seed=1)
      # Initialize all variables
      self.evaluate(tf.compat.v1.global_variables_initializer())
      p_info = self.evaluate(action_step.info)
      self.assertAllEqual(
          p_info.bandit_policy_type,
          [
              [utils.BanditPolicyType.FALCON],
              [utils.BanditPolicyType.FALCON],
          ],
      )
  
imports: from typing import List, Optional, Set
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.policies import falcon_reward_prediction_policy
  from tf_agents.networks import network
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 3 for calling the FalconRewardPredictionPolicyTest obj's underlying member method code with example usage: obj.testBanditPolicyType() without return types