code: def __init__(self):
      super().__init__()
      self.fake_parms = nn.Linear(1, 1)
  
imports: import logging
  import unittest
  from typing import Optional
  import numpy
  import torch
  import torch.nn
  from reagent.core import types
  from reagent.evaluation.doubly_robust_estimator import DoublyRobustEstimator
  from reagent.evaluation.evaluation_data_page import EvaluationDataPage
  from reagent.evaluation.ope_adapter import OPEstimatorAdapter
  from reagent.model_utils.seq2slate_utils import Seq2SlateMode
  from reagent.ope.estimators.contextual_bandits_estimators import SwitchDREstimator, SwitchEstimator
label_desc: Use image node_id 1 to create a new FakeSeq2SlateRewardNetwork object from inherited base classes: nn with example: obj = FakeSeq2SlateRewardNetwork()