code: def test_evaluate_generator_multi_dict_io(self):
      num_steps = 10
      generator = some_data_tensor_generator_dict_io(
          ModelMultiDictIOTest.batch_size
      )
      loss, pred_y = self.model.evaluate_generator(
          generator, steps=num_steps, return_pred=True
      )
      self.assertEqual(type(loss), float)
      self._test_size_and_type_for_generator(
          pred_y, (num_steps * ModelMultiDictIOTest.batch_size, 1)
      )
  
imports: import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from poutyne import Model
  from tests.framework.model.base import ModelFittingTestCase
label_desc: Use image node_id 6 for calling the ModelMultiDictIOTest obj's underlying member method code with example usage: obj.test_evaluate_generator_multi_dict_io() without return types