code: def testGreedyAction(self):
      tf.compat.v1.set_random_seed(1)
      policy = greedy_reward_policy.GreedyRewardPredictionPolicy(
          self._time_step_spec,
          self._action_spec,
          reward_network=DummyNet(self._obs_spec),
      )
      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)
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.assertAllEqual(self.evaluate(action_step.action), [1, 2])
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.bandits.policies import greedy_reward_prediction_policy
  from tf_agents.networks import network
  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 2 for calling the GreedyRewardPredictionPolicyTest obj's underlying member method code with example usage: obj.testGreedyAction() without return types