code: def testActionBatchSizeHigherThanOne(self):
      tf.compat.v1.set_random_seed(1)
      policy = (
          bern_thompson_sampling_policy.BernoulliThompsonSamplingPolicy(
              self._time_step_spec,
              self._action_spec,
              alpha=_prepare_alphas(self._action_spec),
              beta=_prepare_betas(self._action_spec),
          )
      )
      observations = tf.constant([[1], [1]], dtype=tf.float32)
      time_step = ts.restart(observations, batch_size=2)
      action_step = policy.action(time_step, seed=1)
      self.assertEqual(action_step.action.shape.as_list(), [2])
      self.assertEqual(action_step.action.dtype, tf.int32)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.policies import bernoulli_thompson_sampling_policy
  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 8 for calling the BernoulliThompsonSamplingPolicyTest obj's underlying member method code with example usage: obj.testActionBatchSizeHigherThanOne() without return types