code: def cql_setup_late_mixins(
      policy: Policy,
      obs_space: gym.spaces.Space,
      action_space: gym.spaces.Space,
      config: AlgorithmConfigDict,
  ) -> None:
      setup_late_mixins(policy, obs_space, action_space, config)
      if config["lagrangian"]:
          policy.model.log_alpha_prime = (
              policy.model.log_alpha_prime.to(policy.device)
          )
  
imports: import numpy
  import gymnasium
  import logging
  import tree
  from typing import Dict, List, Tuple, Type, Union
  import ray
  import ray.experimental.tf_utils
  from ray.rllib.algorithms.sac.sac_tf_policy import postprocess_trajectory, validate_spaces
  from ray.rllib.algorithms.sac.sac_torch_policy import _get_dist_class, stats, build_sac_model_and_action_dist, optimizer_fn, ComputeTDErrorMixin, setup_late_mixins, action_distribution_fn
  from ray.rllib.models.torch.torch_action_dist import TorchDistributionWrapper
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.policy.policy_template import build_policy_class
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.torch_mixins import TargetNetworkMixin
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.metrics.learner_info import LEARNER_STATS_KEY
  from ray.rllib.utils.typing import LocalOptimizer, TensorType, AlgorithmConfigDict
  from ray.rllib.utils.torch_utils import apply_grad_clipping, convert_to_torch_tensor, concat_multi_gpu_td_errors
label_desc: Use image node_id 7 for calling a global function with example usage: cql_setup_late_mixins(policy, obs_space, action_space, config) without return types