code: def test_non_list(self):
      f = lambda x: x**2 / 2
      g = lambda x: x
      x = np.concatenate(
          [np.linspace(-100, 100, int(1e1)), [0]], axis=0
      )
      y, dydx = self.evaluate(gradient.value_and_gradient(f, x))
      self.assertAllClose(f(x), y, atol=1e-6, rtol=1e-6)
      self.assertAllClose(g(x), dydx, atol=1e-6, rtol=1e-6)
  
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 1 for calling the GradientTest obj's underlying member method code with example usage: obj.test_non_list() without return types