code: def testWrongBetaParamsSize(self):
      tf.compat.v1.set_random_seed(1)
      action_spec = tensor_spec.BoundedTensorSpec((), tf.int32, 10, 20)
      alphas = [
          tf.compat.v2.Variable(
              tf.zeros([], dtype=tf.float32), name="alpha_{}".format(k)
          )
          for k in range(11)
      ]
      betas = [
          tf.compat.v2.Variable(
              tf.zeros([], dtype=tf.float32), name="beta_{}".format(k)
          )
          for k in range(5)
      ]
      with self.assertRaisesRegex(
          ValueError,
          r"The size of alpha parameters is expected to be equal to the size of"
          r" beta parameters",
      ):
          bern_thompson_sampling_policy.BernoulliThompsonSamplingPolicy(
              self._time_step_spec,
              action_spec,
              alpha=alphas,
              beta=betas,
          )
  
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 6 for calling the BernoulliThompsonSamplingPolicyTest obj's underlying member method code with example usage: obj.testWrongBetaParamsSize() without return types