code: def _b_numpy(self):
      return [
          np.array([r, r], dtype=np.float32)
          for r in range(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 5 for calling the LinearBanditPolicyTest obj's underlying member method code with example usage: obj._b_numpy() and returns: unknown