class_docstr: Base class for parametric DQN net builder.
docstr: Returns a TorchScript predictor module
code: def build_serving_module(
      self,
      q_network: ModelBase,
      state_normalization_data: NormalizationData,
      action_normalization_data: NormalizationData,
  ) -> torch.nn.Module:
      """
      Returns a TorchScript predictor module
      """
      state_preprocessor = Preprocessor(
          state_normalization_data.dense_normalization_parameters, False
      )
      action_preprocessor = Preprocessor(
          action_normalization_data.dense_normalization_parameters,
          False,
      )
      dqn_with_preprocessor = ParametricDqnWithPreprocessor(
          q_network.cpu_model().eval(),
          state_preprocessor,
          action_preprocessor,
      )
      return ParametricDqnPredictorWrapper(
          dqn_with_preprocessor=dqn_with_preprocessor
      )
  
file_path: ReAgent/reagent/net_builder/parametric_dqn_net_builder.py
imports: import abc
  import torch
  from reagent.core.fb_checker import IS_FB_ENVIRONMENT
  from reagent.core.parameters import NormalizationData
  from reagent.models.base import ModelBase
  from reagent.prediction.predictor_wrapper import ParametricDqnWithPreprocessor
  from reagent.preprocessing.preprocessor import Preprocessor
label_desc: Use image node_id 2 for calling the ParametricDQNNetBuilder obj's underlying member method code with example usage: obj.build_serving_module(q_network, state_normalization_data, action_normalization_data) and returns: ParametricDqnPredictorWrapper