code: def test_can_take_loop_gradient_inside_xla(self):
      def loss_fn(v):
          return loop_util.trace_scan(
              lambda x, t: x + v,
              0.0,
              tf.range(10),
              trace_fn=lambda x: x,
          )[0]
  
      xla_grad = tf.function(
          lambda v: gradient.value_and_gradient(loss_fn, v)[1],
          jit_compile=True,
      )(0.0)
      self.assertAllClose(xla_grad, 10.0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import loop_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 6 for calling the TraceScanTest obj's underlying member method code with example usage: obj.test_can_take_loop_gradient_inside_xla() and returns: loop_util