code: def get_default_policy_class(
      cls, config: AlgorithmConfig
  ) -> Optional[Type[Policy]]:
      if config["framework"] == "torch":
          from ray.rllib.algorithms.ppo.ppo_torch_policy import (
              PPOTorchPolicy,
          )
  
          return PPOTorchPolicy
      elif config["framework"] == "tf":
          from ray.rllib.algorithms.ppo.ppo_tf_policy import (
              PPOTF1Policy,
          )
  
          return PPOTF1Policy
      else:
          from ray.rllib.algorithms.ppo.ppo_tf_policy import (
              PPOTF2Policy,
          )
  
          return PPOTF2Policy
  
imports: import logging
  from typing import List, Optional, Type, Union, TYPE_CHECKING
  import numpy
  import tree
  from ray.rllib.algorithms.algorithm import Algorithm
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig, NotProvided
  from ray.rllib.core.rl_module.rl_module import SingleAgentRLModuleSpec
  from ray.rllib.evaluation.postprocessing_v2 import postprocess_episodes_to_sample_batch
  from ray.rllib.evaluation.rollout_worker import RolloutWorker
  from ray.rllib.execution.rollout_ops import standardize_fields, synchronous_parallel_sample
  from ray.rllib.execution.train_ops import train_one_step, multi_gpu_train_one_step
  from ray.rllib.policy.policy import Policy
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.deprecation import DEPRECATED_VALUE
  from ray.rllib.utils.metrics.learner_info import LEARNER_STATS_KEY
  from ray.rllib.utils.metrics import NUM_AGENT_STEPS_SAMPLED, NUM_ENV_STEPS_SAMPLED, SYNCH_WORKER_WEIGHTS_TIMER, SAMPLE_TIMER, ALL_MODULES
  from ray.rllib.env.single_agent_episode import SingleAgentEpisode
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.schedules.scheduler import Scheduler
  from ray.rllib.utils.typing import ResultDict
  from ray.util.debug import log_once
label_desc: Use image node_id 2 for calling the PPO obj's underlying member method code with example usage: obj.get_default_policy_class(cls, config) and returns: PPOTorchPolicy, PPOTF1Policy, PPOTF2Policy