message: Updates to Profiler Guide
diff: @@ -51,19 +51,18 @@ class ProfilerOptions(
  collections.namedtuple(
  'ProfilerOptions',
  ['host_tracer_level', 'python_tracer_level', 'device_tracer_level'])):
  - """Options to control profiler behaviors.
  + """Options for finer control over the profiler.
  - A `tf.profiler.ProfilerOptions` hold the knobs to control tf.profiler's
  + Use `tf.profiler.ProfilerOptions` to control `tf.profiler`
  behavior.
  Fields:
  - host_tracer_level: for adjust TraceMe levels. i.e. 1 => critical,
  - 2 => info, 3 => verbose. [default to 2]
  - python_tracer_level: for enable python function call tracing, 1 => enable.
  - 0 => disable [default to 0]
  - device_tracer_level: for adjust device (TPU/GPU) tracer level, 0 => disable
  - 1 => enabled. We may introduce fine-tuned level in the
  - future. [default to 1]
  + host_tracer_level: Adjust CPU tracing level. Values are: 1 - critical info
  + only, 2 - info, 3 - verbose. [default value is 2]
  + python_tracer_level: Toggle tracing of Python function calls. Values are: 1
  + - enabled, 0 - disabled [default value is 0]
  + device_tracer_level: Adjust device (TPU/GPU) tracing level. Values are: 1 -
  + enabled, 0 - disabled [default value is 1]
  """
  def __new__(cls,
  @@ -77,26 +76,29 @@ class ProfilerOptions(
  @tf_export('profiler.experimental.start', v1=[])
  def start(logdir, options=None):
  - """Starts profiling.
  + """Start profiling TensorFlow performance.
  Args:
  - logdir: A log directory read by TensorBoard to export the profile results.
  - options: namedtuple of ProfilerOptions for miscellaneous profiler options.
  + logdir: Profiling results log directory.
  + options: `ProfilerOptions` namedtuple to specify miscellaneous profiler
  + options. See example usage below.
  Raises:
  - AlreadyExistsError: If another profiling session is running.
  + AlreadyExistsError: If a profiling session is already running.
  Example usage:
  ```python
  - tf.profiler.experimental.start(
  - 'logdir_path', tf.profiler.ProfilerOptions(host_tracer_level=2))
  - # do your training here.
  + options = tf.profiler.experimental.ProfilerOptions(host_tracer_level = 3,
  + python_tracer_level = 1,
  + device_tracer_level = 1)
  + tf.profiler.experimental.start('logdir_path', options = options)
  + # Training code here
  tf.profiler.experimental.stop()
  ```
  - Launch TensorBoard and point it to the same logdir you provided to this API.
  - $ tensorboard --logdir=logdir_path
  - Open your browser and go to localhost:6006/#profile to view profiling results.
  + To view the profiling results, launch TensorBoard and point it to `logdir`.
  + Open your browser and go to `localhost:6006/#profile` to view profiling
  + results.
  """
  global _profiler
  