code: def testTimeline(self):
      ops.reset_default_graph()
      outfile = os.path.join(test.get_temp_dir(), "timeline")
      opts = (
          builder(builder.trainable_variables_parameter())
          .with_max_depth(100000)
          .with_step(0)
          .with_timeline_output(outfile)
          .with_accounted_types([".*"])
          .build()
      )
  
      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,
          )
  
          _ = model_analyzer.profile(
              sess.graph, run_meta, cmd="graph", options=opts
          )
  
          with gfile.Open(outfile + "_0", "r") as f:
              # Test that a json file is created.
              # TODO(xpan): tfprof Timeline isn't quite correct on Windows.
              # Investigate why.
              if os.name != "nt":
                  self.assertLess(1000, len(f.read()))
              else:
                  self.assertLess(1, len(f.read()))
  
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 8 for calling the PrintModelAnalysisTest obj's underlying member method code with example usage: obj.testTimeline() without return types