class_docstr: Test the tensorflow interface execute function
  integrates well for both forward and backward execution
class_docstr_tok: ["Test","the","tensorflow","interface","execute","function","integrates","well","for","both","forward","and","backward","execution"]
docstr: Test scalar jacobian calculation
docstr_tok: ["Test","scalar","jacobian","calculation"]
code: def test_scalar_jacobian(self, execute_kwargs, shots, device):
      """Test scalar jacobian calculation"""
      a = tf.Variable(0.1, dtype=tf.float64)
  
      def cost(a):
          tape = qml.tape.QuantumScript(
              [qml.RY(a, 0)], [qml.expval(qml.PauliZ(0))], shots=shots
          )
          return execute([tape], device, **execute_kwargs)[0]
  
      with tf.GradientTape() as tape:
          cost_res = cost(a)
      res = tape.jacobian(cost_res, a)
      assert res.shape == ()  # pylint: disable=no-member
  
      # compare to standard tape jacobian
      tape = qml.tape.QuantumScript(
          [qml.RY(a, wires=0)], [qml.expval(qml.PauliZ(0))]
      )
      tape.trainable_params = [0]
      tapes, fn = param_shift(tape)
      expected = fn(device.execute(tapes))
  
      assert expected.shape == ()
      assert np.allclose(
          res, expected, atol=atol_for_shots(shots), rtol=0
      )
      assert np.allclose(res, -tf.sin(a), atol=atol_for_shots(shots))
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.devices import DefaultQubit
  from pennylane.gradients import param_shift
  from pennylane import execute
label_desc: Use image node_id 2 for calling the TestTensorflowExecuteIntegration obj's underlying member method code with example usage: obj.test_scalar_jacobian(execute_kwargs, shots, device) and returns: execute