code: def test_tensor_evaluate_on_batch_multi_io(self):
      y = (
          torch.rand(ModelMultiIOTest.batch_size, 1),
          torch.rand(ModelMultiIOTest.batch_size, 1),
      )
      x = (
          torch.rand(ModelMultiIOTest.batch_size, 1),
          torch.rand(ModelMultiIOTest.batch_size, 1),
      )
      loss = self.model.evaluate_on_batch(x, y)
      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 7 for calling the ModelMultiIOTest obj's underlying member method code with example usage: obj.test_tensor_evaluate_on_batch_multi_io() without return types