code: def __init__(
      self,
      seq_len: int,
      state_preprocessor: Preprocessor,
      action_preprocessor: Preprocessor,
      net: ModelBase,
  ) -> None:
      super().__init__()
      self.seq_len = seq_len
      self.state_preprocessor = state_preprocessor
      self.action_preprocessor = action_preprocessor
      self.net = net
      self.state_feat_num = len(state_preprocessor.sorted_features)
      self.action_feat_num = len(action_preprocessor.sorted_features)
  
file_path: ReAgent/reagent/prediction/synthetic_reward/synthetic_reward_predictor_wrapper.py
imports: from typing import Tuple
  import torch
  import torch.nn
  from reagent.models.base import ModelBase
  from reagent.preprocessing.preprocessor import Preprocessor
label_desc: Use image node_id 1 to create a new SyntheticRewardPredictorWrapper object from inherited base classes: nn with example: obj = SyntheticRewardPredictorWrapper(seq_len, state_preprocessor, action_preprocessor, net)