code: def testDefunCallBackpropUsingSameObjectForMultipleArguments(self):
      @polymorphic_function.function
      def g(x):
          return backprop.gradients_function(math_ops.multiply, [0, 1])(
              x, x
          )
  
      def np_g(x):
          return [d.numpy() for d in g(x)]
  
      x = constant_op.constant(1.0)
      self.assertAllEqual([1.0, 1.0], np_g(x))
      self.assertAllEqual([1.0, 1.0], np_g(1.0))
  
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 22 for calling the FunctionGradientsTest obj's underlying member method code with example usage: obj.testDefunCallBackpropUsingSameObjectForMultipleArguments() and returns: backprop, unknown