code: def __init__(self, loss_fn):
      @make_tf_callable(self.get_session(), dynamic_shape=True)
      def compute_td_error(
          obs_t,
          act_t,
          rew_t,
          obs_tp1,
          terminateds_mask,
          importance_weights,
      ):
          # Do forward pass on loss to update td errors attribute
          # (one TD-error value per item in batch to update PR weights).
          loss_fn(
              self,
              self.model,
              None,
              {
                  SampleBatch.CUR_OBS: tf.convert_to_tensor(obs_t),
                  SampleBatch.ACTIONS: tf.convert_to_tensor(act_t),
                  SampleBatch.REWARDS: tf.convert_to_tensor(rew_t),
                  SampleBatch.NEXT_OBS: tf.convert_to_tensor(obs_tp1),
                  SampleBatch.TERMINATEDS: tf.convert_to_tensor(
                      terminateds_mask
                  ),
                  PRIO_WEIGHTS: tf.convert_to_tensor(
                      importance_weights
                  ),
              },
          )
          # `self.td_error` is set in loss_fn.
          return self.td_error
  
      self.compute_td_error = compute_td_error
  
imports: import copy
  import gymnasium
  from gymnasium.spaces import Box, Discrete
  from functools import partial
  import logging
  from typing import Dict, List, Optional, Tuple, Type, Union
  import ray
  import ray.experimental.tf_utils
  from ray.rllib.algorithms.dqn.dqn_tf_policy import postprocess_nstep_and_prio, PRIO_WEIGHTS
  from ray.rllib.algorithms.sac.sac_tf_model import SACTFModel
  from ray.rllib.algorithms.sac.sac_torch_model import SACTorchModel
  from ray.rllib.evaluation.episode import Episode
  from ray.rllib.models import ModelCatalog
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.tf_action_dist import Beta, Categorical, DiagGaussian, Dirichlet, SquashedGaussian, TFActionDistribution
  from ray.rllib.policy.policy import Policy
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy.tf_mixins import TargetNetworkMixin
  from ray.rllib.policy.tf_policy_template import build_tf_policy
  from ray.rllib.utils.error import UnsupportedSpaceException
  from ray.rllib.utils.framework import get_variable, try_import_tf
  from ray.rllib.utils.spaces.simplex import Simplex
  from ray.rllib.utils.tf_utils import huber_loss, make_tf_callable
  from ray.rllib.utils.typing import AgentID, LocalOptimizer, ModelGradients, TensorType, AlgorithmConfigDict
label_desc: Use image node_id 1 to create a new ComputeTDErrorMixin object  with example: obj = ComputeTDErrorMixin(loss_fn)