code: def testJit(self):
      self.assertEqual(config.get_optimizer_jit(), "")
  
      # the following function should cause Op fusion to occur. However, there is
      # unfortunately no straightforward way to ensure this. We will just have to
      # settle for creating a test that can trigger JIT.
      @def_function.function
      def fun(a, b):
          c = a * b
          d = c + a
          return d
  
      a = constant_op.constant([2.0, 2.0])
      b = constant_op.constant([2.0, 2.0])
  
      self.evaluate(fun(a, b))
  
      config.set_optimizer_jit("autoclustering")
      self.assertEqual(config.get_optimizer_jit(), "autoclustering")
  
      self.evaluate(fun(a, b))
  
      config.set_optimizer_jit("")
      self.assertEqual(config.get_optimizer_jit(), "")
  
      self.evaluate(fun(a, b))
  
imports: from absl.testing import parameterized
  from tensorflow.core.protobuf import cluster_pb2
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.core.protobuf import rewriter_config_pb2
  from tensorflow.core.protobuf import tensorflow_server_pb2
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_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 errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import test
  from tensorflow.python.util import compat
label_desc: Use image node_id 9 for calling the ConfigTest obj's underlying member method code with example usage: obj.testJit() and returns: d