code: def testPlaysNicelyWithDefun(self):
      with self.session(graph=ops.Graph()) as sess:
          with jit.experimental_jit_scope(True):
  
              @function.Defun(compiled=True, noinline=True)
              def mulop(x1, x2):
                  return x1 * x2
  
              x = constant_op.constant(1.0)
              r = mulop(x, x)
              g_r = gradients.gradients(r, x, name="GA")[0]
  
          # Ensure the forward function is compiled.
          graph_def = r.graph.as_graph_def()
          func_attrs = graph_def.library.function[0].attr
          self.assertTrue(func_attrs["_XlaCompile"].b)
          self.assertEqual(b"jit_scope_0", func_attrs["_XlaScope"].s)
  
          # Ensure the gradient (SymbolicGradient) is compiled, with the same
          # _XlaScope as the function itself.
          grad_op = g_r.op.inputs[0].op
          self.assertTrue(grad_op.get_attr("_XlaCompile"))
          self.assertEqual(
              b"jit_scope_0", grad_op.get_attr("_XlaScope")
          )
  
          # Ensure the ops run: grad(x1*x1) = 2*x1
          self.assertAllClose([1.0, 1.0, 2.0], sess.run([x, r, g_r]))
  
imports: from absl.testing import parameterized
  from tensorflow.python.compiler.xla import jit
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import function
  from tensorflow.python.framework import op_def_registry
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import gradients
  from tensorflow.python.ops import init_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the CompilationEnabledInGradientTest obj's underlying member method code with example usage: obj.testPlaysNicelyWithDefun() and returns: unknown