docstr: Test qinfo measurements with tensorflow.
docstr_tok: ["Test","qinfo","measurements","with","tensorflow","."]
code: def test_qinfo_tf(self):
      """Test qinfo measurements with tensorflow."""
      import tensorflow as tf
  
      phi = tf.Variable(0.9276)
  
      with tf.GradientTape(persistent=True) as grad_tape:
          qs = qml.tape.QuantumScript(
              [qml.IsingXX(phi, wires=(0, 1))], self.measurements
          )
          results = simulate(qs)
  
          result2_real = tf.math.real(results[2])
          result2_imag = tf.math.imag(results[2])
  
      expected = self.expected_results(phi)
      for val1, val2 in zip(results, expected):
          assert qml.math.allclose(val1, val2)
  
      expected_grads = self.expected_grad(phi)
  
      grad0 = grad_tape.jacobian(results[0], phi)
      assert qml.math.allclose(grad0, expected_grads[0])
  
      grad1 = grad_tape.jacobian(results[1], phi)
      assert qml.math.allclose(grad1, expected_grads[1])
  
      grad2_real = grad_tape.jacobian(result2_real, phi)
      grad2_imag = grad_tape.jacobian(result2_imag, phi)
      assert qml.math.allclose(
          np.array(grad2_real) + 1j * np.array(grad2_imag),
          expected_grads[2],
      )
  
      grad3 = grad_tape.jacobian(results[3], phi)
      assert qml.math.allclose(grad3, expected_grads[3])
  
      grad4 = grad_tape.jacobian(results[4], phi)
      assert qml.math.allclose(grad4, expected_grads[4])
  
      grad5 = grad_tape.jacobian(results[5], phi)
      assert qml.math.allclose(grad5, expected_grads[5])
  
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 9 for calling the TestQInfoMeasurements obj's underlying member method code with example usage: obj.test_qinfo_tf() without return types