class_docstr: Tests for the mutual information functions
docstr: Test that the relative entropy transform works for QNodes that take keyword arguments
docstr_tok: ["Test","that","the","relative","entropy","transform","works","for","QNodes","that","take","keyword","arguments"]
code: def test_qnode_kwargs(self, device):
      """Test that the relative entropy transform works for QNodes that take keyword arguments"""
      dev = qml.device(device, wires=2)
  
      @qml.qnode(dev)
      def circuit1(param=0):
          qml.RY(param, wires=0)
          qml.CNOT(wires=[0, 1])
          return qml.state()
  
      @qml.qnode(dev)
      def circuit2(param=0):
          qml.RY(param, wires=0)
          qml.CNOT(wires=[0, 1])
          return qml.state()
  
      rel_ent_circuit = qml.qinfo.relative_entropy(
          circuit1, circuit2, [0], [1]
      )
  
      x, y = np.array(0.4), np.array(0.8)
      actual = rel_ent_circuit(({"param": x},), ({"param": y},))
  
      # compare transform results with analytic results
      expected = (
          np.cos(x / 2) ** 2
          * (np.log(np.cos(x / 2) ** 2) - np.log(np.cos(y / 2) ** 2))
      ) + (
          np.sin(x / 2) ** 2
          * (np.log(np.sin(x / 2) ** 2) - np.log(np.sin(y / 2) ** 2))
      )
  
      assert np.allclose(actual, expected)
  
imports: import pytest
  import pennylane
  from pennylane import numpy
label_desc: Use image node_id 11 for calling the TestRelativeEntropy obj's underlying member method code with example usage: obj.test_qnode_kwargs(device) and returns: qml, qml