code: def test_aux(self):
      x = tf.constant([[2.0]])
  
      def f(x):
          return x**2, x
  
      (y, aux), dx = gradient.value_and_gradient(f, x, has_aux=True)
  
      self.assertAllClose(x**2, y)
      self.assertAllClose(2 * x, dx)
      self.assertAllClose(x, aux)
  
      dx, aux = batch_jacobian(f, x, has_aux=True)
  
      self.assertAllClose((2 * x)[..., tf.newaxis], dx)
      self.assertAllClose(x, aux)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.gradient import batch_jacobian
  from tensorflow_probability.python.math.gradient import value_and_gradient_with_auto_expansion
label_desc: Use image node_id 14 for calling the GradientTest obj's underlying member method code with example usage: obj.test_aux() and returns: unknown,  x