code: def test_incorrect_y_classes(average):
      pr = Precision(average=average)
  
      assert pr._updated is False
  
      y_pred = torch.randint(0, 2, size=(10, 4)).float()
      y = torch.randint(4, 5, size=(10,)).long()
  
      with pytest.raises(ValueError):
          pr.update((y_pred, y))
  
      assert pr._updated is False
  
imports: import warnings
  import pytest
  import torch
  from sklearn.exceptions import UndefinedMetricWarning
  from sklearn.metrics import precision_score
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics import Precision
label_desc: Use image node_id 12 for calling a global function with example usage: test_incorrect_y_classes(average) without return types