class_docstr: Test that the wrapped NumPy functionality integrates well
  with standard NumPy functions.
class_docstr_tok: ["Test","that","the","wrapped","NumPy","functionality","integrates","well","with","standard","NumPy","functions","."]
docstr: Test that a tensor is returned if the array ufunc method returns
  multiple results.
docstr_tok: ["Test","that","a","tensor","is","returned","if","the","array","ufunc","method","returns","multiple","results","."]
code: def test_multi_output_array_ufunc(self):
      """Test that a tensor is returned if the array ufunc method returns
      multiple results."""
  
      class _ufunc:
          # pylint: disable=unused-argument,too-few-public-methods
          def __init__(self, *args, **kwargs):
              self.nout = 2
  
          def __call__(self, *args, **kwargs):
              return [True, True]
  
      x = np.array([[1, 2], [3, 4]], requires_grad=False)
      res = x.__array_ufunc__(_ufunc(), "__call__")
      assert isinstance(res, tuple)
      assert len(res) == 2
  
imports: import numpy
  import pytest
  from autograd.numpy.numpy_boxes import ArrayBox
  import pennylane
  from pennylane import numpy
  from pennylane.numpy.tensor import tensor_to_arraybox
label_desc: Use image node_id 18 for calling the TestNumpyIntegration obj's underlying member method code with example usage: obj.test_multi_output_array_ufunc() and returns: list