code: def _num_samples_per_arm(self):
      a_for_one_arm = tf.constant([1], dtype=tf.float32)
      return [a_for_one_arm] * self._num_actions
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import itertools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.policies import linear_bandit_policy
  from tf_agents.bandits.specs import utils
  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
label_desc: Use image node_id 6 for calling the LinearBanditPolicyTest obj's underlying member method code with example usage: obj._num_samples_per_arm() and returns: unknown