code: def setup_mid_mixins(
      policy: Policy, obs_space, action_space, config
  ) -> None:
      LearningRateSchedule.__init__(
          policy, config["lr"], config["lr_schedule"]
      )
      ComputeTDErrorMixin.__init__(policy)
  
imports: from typing import Dict
  import gymnasium
  import numpy
  import ray
  from ray.rllib.algorithms.dqn.distributional_q_tf_model import DistributionalQTFModel
  from ray.rllib.algorithms.simple_q.utils import Q_SCOPE, Q_TARGET_SCOPE
  from ray.rllib.evaluation.postprocessing import adjust_nstep
  from ray.rllib.models import ModelCatalog
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.tf_action_dist import get_categorical_class_with_temperature
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.tf_mixins import LearningRateSchedule, TargetNetworkMixin
  from ray.rllib.policy.tf_policy_template import build_tf_policy
  from ray.rllib.utils.error import UnsupportedSpaceException
  from ray.rllib.utils.exploration import ParameterNoise
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.tf_utils import huber_loss, l2_loss, make_tf_callable, minimize_and_clip, reduce_mean_ignore_inf
  from ray.rllib.utils.typing import AlgorithmConfigDict, ModelGradients, TensorType
label_desc: Use image node_id 7 for calling a global function with example usage: setup_mid_mixins(policy, obs_space, action_space, config) without return types