code: def before_loss_init(
      policy: Policy,
      obs_space: gym.spaces.Space,
      action_space: gym.spaces.Space,
      config: AlgorithmConfigDict,
  ) -> None:
      ComputeTDErrorMixin.__init__(policy)
  
imports: from typing import Dict, List, Optional, Tuple
  import gymnasium
  import ray
  from ray.rllib.algorithms.dqn.dqn_tf_policy import PRIO_WEIGHTS, build_q_model, clip_gradients, compute_q_values, postprocess_nstep_and_prio
  from ray.rllib.models.action_dist import ActionDistribution
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.tf_action_dist import Categorical
  from ray.rllib.models.torch.torch_action_dist import TorchCategorical
  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, ModelInputDict, TensorType
label_desc: Use image node_id 9 for calling a global function with example usage: before_loss_init(policy, obs_space, action_space, config) without return types