code: def testAdvisor(self):
      ops.reset_default_graph()
  
      with session.Session(
          config=self._no_rewrite_session_config()
      ) as sess:
          x = lib.BuildFullModel()
  
          self.evaluate(variables.global_variables_initializer())
          run_meta = config_pb2.RunMetadata()
          _ = sess.run(
              x,
              options=config_pb2.RunOptions(
                  trace_level=config_pb2.RunOptions.FULL_TRACE
              ),
              run_metadata=run_meta,
          )
  
          advice_pb = model_analyzer.advise(sess.graph, run_meta)
          self.assertTrue(
              "AcceleratorUtilizationChecker" in advice_pb.checkers
          )
          self.assertTrue(
              "ExpensiveOperationChecker" in advice_pb.checkers
          )
          self.assertTrue("OperationChecker" in advice_pb.checkers)
  
          checker = advice_pb.checkers["AcceleratorUtilizationChecker"]
          if test.is_gpu_available():
              self.assertGreater(len(checker.reports), 0)
          else:
              self.assertEqual(len(checker.reports), 0)
          checker = advice_pb.checkers["ExpensiveOperationChecker"]
          self.assertGreater(len(checker.reports), 0)
  
imports: import gzip
  import io
  import os
  import random
  import re
  import numpy
  from tensorflow.core.profiler import profile_pb2
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.core.protobuf import rewriter_config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import test
  from tensorflow.python.profiler import model_analyzer
  from tensorflow.python.profiler import option_builder
  from tensorflow.python.profiler import profile_context
  from tensorflow.python.profiler.internal import model_analyzer_testlib
  from tensorflow.python.util import compat
label_desc: Use image node_id 10 for calling the PrintModelAnalysisTest obj's underlying member method code with example usage: obj.testAdvisor() without return types