code: def setUp(self):
      super().setUp()
      torch.manual_seed(42)
      self.pytorch_network = MultiIOModel(num_input=1, num_output=2)
      self.loss_function = nn.MSELoss()
      self.optimizer = torch.optim.SGD(
          self.pytorch_network.parameters(), lr=1e-3
      )
  
      self.model = Model(
          self.pytorch_network,
          self.optimizer,
          lambda y_pred, y_true: self.loss_function(
              y_pred[0], y_true[0]
          )
          + self.loss_function(y_pred[1], y_true[1]),
          batch_metrics=self.batch_metrics,
          epoch_metrics=self.epoch_metrics,
      )
  
imports: import numpy
  import torch
  import torch.nn
  from torch.utils.data import DataLoader
  from poutyne import Model, TensorDataset
  from tests.framework.model.base import ModelFittingTestCase, MultiIOModel
label_desc: Use image node_id 1 for calling the ModelMultiOutputTest obj's underlying member method code with example usage: obj.setUp() without return types