code: def test_evaluate_multi_input(self):
      x = (
          torch.rand(ModelMultiInputTest.evaluate_dataset_len, 1),
          torch.rand(ModelMultiInputTest.evaluate_dataset_len, 1),
      )
      y = torch.rand(ModelMultiInputTest.evaluate_dataset_len, 1)
      loss = self.model.evaluate(
          x, y, batch_size=ModelMultiInputTest.batch_size
      )
      self.assertEqual(type(loss), float)
  
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 7 for calling the ModelMultiInputTest obj's underlying member method code with example usage: obj.test_evaluate_multi_input() without return types