code: def test_predict_with_np_array_multi_output(self):
      x = np.random.rand(
          ModelMultiOutputTest.evaluate_dataset_len, 1
      ).astype(np.float32)
  
      pred_y = self.model.predict(
          x, batch_size=ModelMultiOutputTest.batch_size
      )
      for pred in pred_y:
          self.assertEqual(
              pred.shape, (ModelMultiOutputTest.evaluate_dataset_len, 1)
          )
  
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 11 for calling the ModelMultiOutputTest obj's underlying member method code with example usage: obj.test_predict_with_np_array_multi_output() without return types