code: def test_simple_input_no_auto_unpack(self):
      x = [1.0, 2.0, 3.0]
      y, dydx = self.evaluate(
          gradient.value_and_gradient(
              tf.math.log, x, auto_unpack_single_arg=False
          )
      )
      self.assertAllClose(np.log(x), y, atol=1e-6, rtol=1e-6)
      self.assertAllClose(1.0 / np.array(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 7 for calling the GradientTest obj's underlying member method code with example usage: obj.test_simple_input_no_auto_unpack() without return types