code: def setUp(self):
      # self.model = nn.Sequential(
      #     nn.Linear(10, 8), nn.ReLU(), nn.Dropout(), nn.Linear(8, 1), nn.Sigmoid()
      # )
      self.model = SimpleModel()
      self.criterion = nn.BCEWithLogitsLoss()
      self.wrapper = ModelWrapper(self.model, self.criterion)
      self.optim = torch.optim.SGD(self.wrapper.get_params(), 0.01)
      self.dataset = DummyDataset()
  
imports: import math
  import unittest
  from unittest.mock import Mock
  import numpy
  import pytest
  import torch
  import torchmetrics
  from torch import nn
  from torch.utils.data import Dataset, DataLoader
  from baal.modelwrapper import ModelWrapper, mc_inference
  from baal.utils.metrics import ClassificationReport
label_desc: Use image node_id 1 for calling the ModelWrapperTest obj's underlying member method code with example usage: obj.setUp() without return types