code: def test_ndarray_train_on_batch_dict_output(self):
      x = np.random.rand(ModelDictOutputTest.batch_size, 1).astype(
          np.float32
      )
      y1 = np.random.rand(ModelDictOutputTest.batch_size, 1).astype(
          np.float32
      )
      y2 = np.random.rand(ModelDictOutputTest.batch_size, 1).astype(
          np.float32
      )
      loss = self.model.train_on_batch(x, (y1, y2))
      self.assertEqual(type(loss), float)
  
file_path: poutyne/tests/framework/model/test_dict_output.py
imports: import numpy
  import torch
  import torch.nn
  from poutyne import Model
  from tests.framework.model.base import ModelFittingTestCase
label_desc: Use image node_id 3 for calling the ModelDictOutputTest obj's underlying member method code with example usage: obj.test_ndarray_train_on_batch_dict_output() without return types