code: def testSymbolicHigherOrder(self):
      @polymorphic_function.function
      def f(x, order):
          y = polymorphic_function.function(lambda: math_ops.cos(x))()
          for _ in range(order):
              (y,) = gradients_impl.gradients(y, [x])
          return y
  
      for order, expected in enumerate(_COS_DERIVATIVES):
          self.assertAllClose(
              expected(constant_op.constant(1.0)),
              f(constant_op.constant(1.0), order),
          )
  
imports: from absl.testing import parameterized
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.eager.polymorphic_function import polymorphic_function
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_grad
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the FunctionGradientsTest obj's underlying member method code with example usage: obj.testSymbolicHigherOrder() and returns: y