class_docstr: Run and report benchmark results.
  
  The first run is without any profilng.
  Second run is with xprof and python trace. Third run is with xprof without
  python trace. Note: xprof runs are with fewer iterations.
code: def run_with_xprof(
      self,
      enable_python_trace,
      run_benchmark,
      func,
      num_iters_xprof,
      execution_mode,
      suid,
  ):
      if enable_python_trace:
          options = profiler.ProfilerOptions(python_tracer_level=1)
          logdir = os.path.join(
              flags.FLAGS.logdir, suid + "_with_python"
          )
      else:
          options = profiler.ProfilerOptions(python_tracer_level=0)
          logdir = os.path.join(flags.FLAGS.logdir, suid)
      with profiler.Profile(logdir, options):
          total_time = run_benchmark(
              func, num_iters_xprof, execution_mode
          )
      us_per_example = float(
          "{0:.3f}".format(total_time * 1e6 / num_iters_xprof)
      )
      return logdir, us_per_example
  
file_path: tensorflow-upstream/tensorflow/python/eager/benchmarks_test_base.py
imports: import os
  import uuid
  from tensorflow.python.eager import test
  from tensorflow.python.platform import flags
  from tensorflow.python.profiler import profiler_v2
label_desc: Use image node_id 1 for calling the MicroBenchmarksBase obj's underlying member method code with example usage: obj.run_with_xprof(enable_python_trace, run_benchmark, func, num_iters_xprof, execution_mode, suid) and returns: logdir,  us_per_example