class_docstr: Bandit Algorithm using ThompsonSampling exploration.
code: def get_default_policy_class(
      cls, config: AlgorithmConfig
  ) -> Optional[Type[Policy]]:
      if config["framework"] == "torch":
          return BanditTorchPolicy
      elif config["framework"] == "tf2":
          return BanditTFPolicy
      else:
          raise NotImplementedError(
              "Only `framework=[torch|tf2]` supported!"
          )
  
imports: import logging
  from typing import Optional, Type, Union
  from rllib_bandit.bandit.bandit_tf_policy import BanditTFPolicy
  from rllib_bandit.bandit.bandit_torch_policy import BanditTorchPolicy
  from ray.rllib.algorithms.algorithm import Algorithm
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.policy.policy import Policy
  from ray.rllib.utils.annotations import override
label_desc: Use image node_id 2 for calling the BanditLinTS obj's underlying member method code with example usage: obj.get_default_policy_class(cls, config) and returns: BanditTorchPolicy, BanditTFPolicy