code: def _build_binary_difference_scorer(
      self,
      network,
      normalization_data_map: Dict[str, NormalizationData],
  ):
      assert network is not None
      net_builder = self.net_builder.value
      return net_builder.build_binary_difference_scorer(
          network,
          normalization_data_map[NormalizationKey.STATE],
          action_names=self.action_names,
          state_feature_config=self.state_feature_config,
      )
  
imports: import logging
  from typing import Dict, Optional
  import torch
  from reagent.core.dataclasses import dataclass, field
  from reagent.core.parameters import NormalizationData, NormalizationKey, param_hash
  from reagent.evaluation.evaluator import get_metrics_to_score
  from reagent.model_managers.discrete_dqn_base import DiscreteDQNBase
  from reagent.net_builder.discrete_dqn.dueling import Dueling
  from reagent.net_builder.discrete_dqn.fully_connected import FullyConnected
  from reagent.net_builder.unions import DiscreteDQNNetBuilder__Union
  from reagent.prediction.cfeval.predictor_wrapper import BanditRewardNetPredictorWrapper
  from reagent.reporting.discrete_dqn_reporter import DiscreteDQNReporter
  from reagent.training import DQNTrainer, DQNTrainerParameters, ReAgentLightningModule
  from reagent.training.dqn_trainer_base import DQNTrainerBaseLightning
  from reagent.workflow.types import RewardOptions
label_desc: Use image node_id 9 for calling the DiscreteDQN obj's underlying member method code with example usage: obj._build_binary_difference_scorer(network, normalization_data_map) and returns: net_builder