class_docstr: Test the Hadamard gradient transform and edge cases such as non diff parameters, auxiliary wires, etc...
class_docstr_tok: ["Test","the","Hadamard","gradient","transform","and","edge","cases","such","as","non","diff","parameters",",","auxiliary","wires",",","etc","..."]
docstr: Test that the transform works correctly when the diff method for every parameter is
  identified to be 0, and that no tapes were generated.
code: def test_all_zero_diff_methods_tape(self):
      """Test that the transform works correctly when the diff method for every parameter is
      identified to be 0, and that no tapes were generated."""
      dev = qml.device("default.qubit", wires=3)
  
      params = np.array([0.5, 0.5, 0.5], requires_grad=True)
  
      with qml.queuing.AnnotatedQueue() as q:
          qml.Rot(*params, wires=0)
          qml.probs([2, 3])
  
      tape = qml.tape.QuantumScript.from_queue(q)
  
      res_hadamard, tapes = grad_fn(tape, dev)
  
      assert tapes == []
  
      assert isinstance(res_hadamard, tuple)
  
      assert len(res_hadamard) == 3
  
      assert isinstance(res_hadamard[0], np.ndarray)
      assert res_hadamard[0].shape == (4,)
      assert np.allclose(res_hadamard[0], 0)
  
      assert isinstance(res_hadamard[1], np.ndarray)
      assert res_hadamard[1].shape == (4,)
      assert np.allclose(res_hadamard[1], 0)
  
      assert isinstance(res_hadamard[2], np.ndarray)
      assert res_hadamard[2].shape == (4,)
      assert np.allclose(res_hadamard[2], 0)
  
imports: import pytest
  import pennylane
  from pennylane import numpy
label_desc: Use image node_id 21 for calling the TestHadamardGradEdgeCases obj's underlying member method code with example usage: obj.test_all_zero_diff_methods_tape() without return types