code: def test_multilabel_wrong_inputs():
      acc = Accuracy(is_multilabel=True)
  
      with pytest.raises(ValueError):
          # incompatible shapes
          acc.update(
              (
                  torch.randint(0, 2, size=(10,)),
                  torch.randint(0, 2, size=(10,)).long(),
              )
          )
  
      with pytest.raises(ValueError):
          # incompatible y_pred
          acc.update(
              (
                  torch.rand(10, 5),
                  torch.randint(0, 2, size=(10, 5)).long(),
              )
          )
  
      with pytest.raises(ValueError):
          # incompatible y
          acc.update(
              (torch.randint(0, 5, size=(10, 5, 6)), torch.rand(10))
          )
  
      with pytest.raises(ValueError):
          # incompatible binary shapes
          acc.update(
              (
                  torch.randint(0, 2, size=(10, 1)),
                  torch.randint(0, 2, size=(10, 1)).long(),
              )
          )
  
imports: import os
  import pytest
  import torch
  from packaging.version import Version
  from sklearn.metrics import accuracy_score
  import ignite.distributed
  from ignite.engine import Engine
  from ignite.exceptions import NotComputableError
  from ignite.metrics import Accuracy
label_desc: Use image node_id 11 for calling a global function with example usage: test_multilabel_wrong_inputs() without return types