class_docstr: Base class for Synthetic Reward net builder.
class_docstr_tok: ["Base","class","for","Synthetic","Reward","net","builder","."]
code: def build_synthetic_reward_network(
      self,
      # dense state features
      state_normalization_data: NormalizationData,
      # dense action features
      action_normalization_data: Optional[NormalizationData] = None,
      discrete_action_names: Optional[List[str]] = None,
      # sparse state features will be read from state_feature_config
      state_feature_config: Optional[rlt.ModelFeatureConfig] = None,
      # sparse action features will be read from action_feature_config
      action_feature_config: Optional[rlt.ModelFeatureConfig] = None,
  ) -> ModelBase:
      pass
  
file_path: ReAgent/reagent/net_builder/synthetic_reward_net_builder.py
imports: import abc
  from typing import List, Optional
  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.preprocessing.preprocessor import Preprocessor
label_desc: Use image node_id 1 for calling the SyntheticRewardNetBuilder obj's underlying member method code with example usage: obj.build_synthetic_reward_network(state_normalization_data, action_normalization_data, discrete_action_names, state_feature_config, action_feature_config) without return types