code: def build_slateq_model(
      policy: Policy,
      obs_space: gym.spaces.Space,
      action_space: gym.spaces.Space,
      config: AlgorithmConfigDict,
  ) -> SlateQTFModel:
      """Build models for the SlateQTFPolicy.
  
      Args:
          policy: The policy, which will use the model for optimization.
          obs_space: The policy's observation space.
          action_space: The policy's action space.
          config: The Algorithm's config dict.
  
      Returns:
          The slate-Q specific Q-model instance.
      """
      model = SlateQTFModel(
          obs_space,
          action_space,
          num_outputs=action_space.nvec[0],
          model_config=config["model"],
          name="slateq_model",
          fcnet_hiddens_per_candidate=config[
              "fcnet_hiddens_per_candidate"
          ],
      )
  
      policy.target_model = SlateQTFModel(
          obs_space,
          action_space,
          num_outputs=action_space.nvec[0],
          model_config=config["model"],
          name="target_slateq_model",
          fcnet_hiddens_per_candidate=config[
              "fcnet_hiddens_per_candidate"
          ],
      )
  
      return model
  
imports: import functools
  import logging
  from typing import Dict
  import gymnasium
  import numpy
  from rllib_slate_q.slate_q.slateq_tf_model import SlateQTFModel
  from ray.rllib.algorithms.dqn.dqn_tf_policy import clip_gradients
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.tf_action_dist import SlateMultiCategorical
  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.framework import try_import_tf
  from ray.rllib.utils.tf_utils import huber_loss
  from ray.rllib.utils.typing import AlgorithmConfigDict, TensorType
label_desc: Use image node_id 1 for calling a global function with example usage: build_slateq_model(policy, obs_space, action_space, config) and returns: model