code: def testDistribution(self):
      policy = q_policy.QPolicy(
          self._time_step_spec, self._action_spec, q_network=DummyNet()
      )
  
      observations = tf.constant([[1, 2]], dtype=tf.float32)
      time_step = ts.restart(observations, batch_size=1)
      distribution_step = policy.distribution(time_step)
      mode = distribution_step.action.mode()
      self.evaluate(tf.compat.v1.global_variables_initializer())
      # The weights of index 0 are all 1 and the weights of index 1 are all 1.5,
      # so the Q values of index 1 will be higher.
      self.assertAllEqual([1], self.evaluate(mode))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.networks import network
  from tf_agents.networks import q_network
  from tf_agents.policies import q_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 8 for calling the QPolicyTest obj's underlying member method code with example usage: obj.testDistribution() without return types