code: def __init__(self, config):
      self.kl_coeff_val = (
          [config["kl_coeff"]]
          * config["inner_adaptation_steps"]
          * config["num_workers"]
      )
      self.kl_target = self.config["kl_target"]
  
imports: import logging
  from typing import Dict, List, Type, Union
  import ray
  from ray.rllib.algorithms.ppo.ppo_tf_policy import validate_config
  from ray.rllib.evaluation.postprocessing import Postprocessing, compute_gae_for_sample_batch
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.torch.torch_action_dist import TorchDistributionWrapper
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.torch_mixins import ValueNetworkMixin
  from ray.rllib.policy.torch_policy_v2 import TorchPolicyV2
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.torch_utils import apply_grad_clipping
  from ray.rllib.utils.typing import TensorType
label_desc: Use image node_id 1 to create a new KLCoeffMixin object  with example: obj = KLCoeffMixin(config)