docstr: Tests autograd derivatives with qinfo measurements.
  Only simulates one measurement at a time due to autograd differentiation limitations.
docstr_tok: ["Tests","autograd","derivatives","with","qinfo","measurements",".","Only","simulates","one","measurement","at","a","time","due","to","autograd","differentiation","limitations","."]
code: def test_qinfo_autograd_backprop(self):
      """Tests autograd derivatives with qinfo measurements.
      Only simulates one measurement at a time due to autograd differentiation limitations.
      """
  
      phi = qml.numpy.array(0.263)
  
      def f(x, m_ind, real=True):
          qs = qml.tape.QuantumScript(
              [qml.IsingXX(x, wires=(0, 1))], [self.measurements[m_ind]]
          )
          out = simulate(qs)
          return qml.math.real(out) if real else qml.math.imag(out)
  
      expected_grads = self.expected_grad(phi)
  
      for i in (0, 1, 3, 4, 5):  # skip density matrix on both wires
          g = qml.jacobian(f)(phi, i, real=True)
          assert qml.math.allclose(expected_grads[i], g)
  
      # density matrix on both wires case
      g_real = qml.jacobian(f)(phi, 2, True)
      g_imag = qml.jacobian(f)(phi, 2, False)
      assert qml.math.allclose(g_real + 1j * g_imag, expected_grads[2])
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.devices.qubit import simulate, get_final_state, measure_final_state
label_desc: Use image node_id 6 for calling the TestQInfoMeasurements obj's underlying member method code with example usage: obj.test_qinfo_autograd_backprop() and returns: unknown