class_docstr: Base class for discrete actor net builder.
docstr: Returns a TorchScript predictor module
code: def build_serving_module(
      self,
      actor: ModelBase,
      state_feature_config: rlt.ModelFeatureConfig,
      state_normalization_data: NormalizationData,
      action_feature_ids: List[int],
  ) -> torch.nn.Module:
      """
      Returns a TorchScript predictor module
      """
  
      state_preprocessor = Preprocessor(
          state_normalization_data.dense_normalization_parameters,
          use_gpu=False,
      )
      actor_with_preprocessor = ActorWithPreprocessor(
          actor.cpu_model().eval(),
          state_preprocessor,
          state_feature_config,
      )
      return ActorPredictorWrapper(
          actor_with_preprocessor,
          state_feature_config,
          action_feature_ids,
      )
  
file_path: ReAgent/reagent/net_builder/discrete_actor_net_builder.py
imports: import abc
  from typing import List
  import reagent.core.types
  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 ActorWithPreprocessor
  from reagent.preprocessing.preprocessor import Preprocessor
label_desc: Use image node_id 2 for calling the DiscreteActorNetBuilder obj's underlying member method code with example usage: obj.build_serving_module(actor, state_feature_config, state_normalization_data, action_feature_ids) and returns: ActorPredictorWrapper