code: def testIteratedGradientsNestedWithVariable(self):
      def _grad(f):
          def _grad_function():
              with backprop.GradientTape() as tape:
                  primal_out = f()
              (g,) = tape.gradient(primal_out, tape.watched_variables())
              return g
  
          return _grad_function
  
      v = variables.Variable(2.0)
  
      @polymorphic_function.function
      def _forward():
          return math_ops.cos(v)
  
      f = _forward
  
      two = constant_op.constant(2.0)
  
      for expected in _COS_DERIVATIVES:
          self.assertAllClose(expected(two), f())
          self.assertAllClose(
              expected(two), polymorphic_function.function(f)()
          )
          f = _grad(f)
  
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 7 for calling the FunctionGradientsTest obj's underlying member method code with example usage: obj.testIteratedGradientsNestedWithVariable() and returns: _grad_function, math_ops, g