code: def test_ndarray_train_on_batch_multi_io(self):
      x1 = np.random.rand(ModelMultiIOTest.batch_size, 1).astype(
          np.float32
      )
      x2 = np.random.rand(ModelMultiIOTest.batch_size, 1).astype(
          np.float32
      )
      y1 = np.random.rand(ModelMultiIOTest.batch_size, 1).astype(
          np.float32
      )
      y2 = np.random.rand(ModelMultiIOTest.batch_size, 1).astype(
          np.float32
      )
      loss = self.model.train_on_batch((x1, x2), (y1, y2))
      self.assertEqual(type(loss), float)
  
file_path: poutyne/tests/framework/model/test_multi_io.py
imports: import numpy
  import torch
  import torch.nn
  from poutyne import Model
  from tests.framework.model.base import ModelFittingTestCase, MultiIOModel
label_desc: Use image node_id 5 for calling the ModelMultiIOTest obj's underlying member method code with example usage: obj.test_ndarray_train_on_batch_multi_io() without return types