code: def setUp(self):
      super(AgentTest, self).setUp()
      tf.compat.v1.enable_resource_variables()
      self._obs_spec = tensor_spec.TensorSpec([2], tf.float32)
      self._time_step_spec = ts.time_step_spec(self._obs_spec)
      self._action_spec = tensor_spec.BoundedTensorSpec(
          dtype=tf.int32, shape=(), minimum=0, maximum=2
      )
      self._observation_spec = self._time_step_spec.observation
      self._num_samples_list = [
          tf.compat.v2.Variable(
              0, dtype=tf.int64, name="num_samples_0"
          ),
          tf.compat.v2.Variable(
              0, dtype=tf.int64, name="num_samples_1"
          ),
          tf.compat.v2.Variable(
              0, dtype=tf.int64, name="num_samples_2"
          ),
      ]
      self._per_arm_num_samples_list = [
          tf.compat.v2.Variable(0, dtype=tf.int64, name="num_samples")
      ]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.bandits.agents import greedy_reward_prediction_agent
  from tf_agents.bandits.agents import neural_boltzmann_agent
  from tf_agents.bandits.agents import neural_epsilon_greedy_agent
  from tf_agents.bandits.agents import neural_falcon_agent
  from tf_agents.bandits.drivers import driver_utils
  from tf_agents.bandits.networks import global_and_arm_feature_network
  from tf_agents.bandits.policies import constraints
  from tf_agents.bandits.specs import utils
  from tf_agents.networks import network
  from tf_agents.policies import utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
label_desc: Use image node_id 1 for calling the AgentTest obj's underlying member method code with example usage: obj.setUp() without return types