code: def test_fitting_tensor_generator_multi_output(self):
      train_generator = some_data_tensor_generator_multi_output(
          ModelMultiOutputTest.batch_size
      )
      valid_generator = some_data_tensor_generator_multi_output(
          ModelMultiOutputTest.batch_size
      )
      logs = self.model.fit_generator(
          train_generator,
          valid_generator,
          epochs=ModelMultiOutputTest.epochs,
          steps_per_epoch=ModelMultiOutputTest.steps_per_epoch,
          validation_steps=ModelMultiOutputTest.steps_per_epoch,
          callbacks=[self.mock_callback],
      )
      params = {
          "epochs": ModelMultiOutputTest.epochs,
          "steps": ModelMultiOutputTest.steps_per_epoch,
          "valid_steps": ModelMultiOutputTest.steps_per_epoch,
      }
      self._test_callbacks_train(params, logs)
  
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 2 for calling the ModelMultiOutputTest obj's underlying member method code with example usage: obj.test_fitting_tensor_generator_multi_output() without return types