code: def setUp(self):
      class MultiOutModel(nn.Module):
          def __init__(self):
              super().__init__()
              self.model = SimpleModel()
  
          def forward(self, x):
              return [self.model(x)] * 2
  
      self._crit = nn.MSELoss()
      self.criterion = lambda x, y: self._crit(x[0], y) + self._crit(
          x[1], y
      )
      self.model = MultiOutModel()
      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 ModelWrapperMultiOutMultiInTest obj's underlying member method code with example usage: obj.setUp() and returns: unknown