class_docstr: Linear Bandit Policy to be used by LinUCB, LinTS and possibly others.
class_docstr_tok: ["Linear","Bandit","Policy","to","be","used","by","LinUCB",",","LinTS","and","possibly","others","."]
code: def _variables(self):
      all_vars = [
          self._cov_matrix,
          self._data_vector,
          self._theta,
          self._num_samples,
          self._eig_matrix,
          self._eig_vals,
      ]
      return [
          v
          for v in tf.nest.flatten(all_vars)
          if isinstance(v, tf.Variable)
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import enum
  from typing import Optional, Sequence, Text, Tuple
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.policies import constraints
  from tf_agents.bandits.policies import linalg
  from tf_agents.bandits.specs import utils
  from tf_agents.policies import tf_policy
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.typing import types
label_desc: Use image node_id 2 for calling the LinearBanditPolicy obj's underlying member method code with example usage: obj._variables() and returns: unknown