class_docstr: Test that the supported configurations in the documentation
  matches the supported configurations in the code.
  
  Also test that the supported configurations do not raise any errors and
  the unsupported configurations raise the expected errors or otherwise
  behave as expected.
  
  These tests do not test for correctness.
class_docstr_tok: ["Test","that","the","supported","configurations","in","the","documentation","matches","the","supported","configurations","in","the","code",".","Also","test","that","the","supported","configurations","do","not","raise","any","errors","and","the","unsupported","configurations","raise","the","expected","errors","or","otherwise","behave","as","expected",".","These","tests","do","not","test","for","correctness","."]
docstr: Test diff_method=parameter-shift fails for all interfaces and
  the return_types State and DensityMatrix
docstr_tok: ["Test","diff_method=parameter-shift","fails","for","all","interfaces","and","the","return_types","State","and","DensityMatrix"]
code: def test_all_paramshift_state(
      self, interface, return_type, shots, wire_specs
  ):
      """Test diff_method=parameter-shift fails for all interfaces and
      the return_types State and DensityMatrix"""
      msg = (
          "Computing the gradient of circuits that return the state with the "
          "parameter-shift rule gradient transform is not supported."
      )
      complex = return_type == "StateVector"
  
      # with pytest.raises(ValueError, match=msg):
      circuit = get_qnode(
          interface, "parameter-shift", return_type, shots, wire_specs
      )
      x = get_variable(interface, wire_specs, complex=complex)
      if shots is not None:
          with pytest.raises(
              qml.DeviceError, match="not accepted with finite shots"
          ):
              compute_gradient(
                  x, interface, circuit, return_type, complex=complex
              )
      else:
          if interface == "torch" and return_type == "StateVector":
              pytest.xfail(reason="see pytorch/pytorch/issues/94397")
          with pytest.raises(ValueError, match=msg):
              compute_gradient(
                  x, interface, circuit, return_type, complex=complex
              )
  
imports: import pytest
  import pennylane
  from pennylane import numpy
  from pennylane import QuantumFunctionError
  from pennylane.measurements import Probability, Expectation, Variance, Sample, VnEntropy, MutualInfo
  from pennylane.measurements.measurements import ObservableReturnTypes
label_desc: Use image node_id 9 for calling the TestSupportedConfs obj's underlying member method code with example usage: obj.test_all_paramshift_state(interface, return_type, shots, wire_specs) without return types