code: def predict(self, x: Tensor, device=None) -> PredictResults:
      if self._model is not None:
          self._model.eval()
          proba = torch.as_tensor(
              self._model(x), dtype=torch.float, device=device
          )
          return PredictResults(torch.argmax(proba, 1), proba)
      else:
          raise Exception("mode not trained")
  
imports: import logging
  import math
  import time
  from typing import Optional
  import numpy
  import torch
  from reagent.ope.estimators.types import PredictResults, Trainer, TrainingData
  from sklearn.linear_model import Lasso, LogisticRegression, SGDClassifier
  from sklearn.metrics import accuracy_score, mean_squared_error
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from torch import Tensor
label_desc: Use image node_id 4 for calling the NNTrainer obj's underlying member method code with example usage: obj.predict(x, device) and returns: PredictResults