code: def to(self, device):
      self._model.to(device)
  
imports: import logging
  import gym
  import torch
  from reagent.ope.estimators.sequential_estimators import Action, ActionDistribution, ActionSpace, IPSEstimator, Model, NeuralDualDICE, RandomRLPolicy, RewardProbability, RLEstimatorInput, RLPolicy, State, StateDistribution, Transition
  from reagent.ope.utils import RunningAverage
label_desc: Use image node_id 3 for calling the ModelWrapper obj's underlying member method code with example usage: obj.to(device) without return types