tf.compat.v1.profiler.Profiler TensorFlow multi-step profiler. 
tf.compat.v1.profiler.Profiler(
    graph=None, op_log=None
)
 https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/README.md Typical use case:
  # Currently we are only allowed to create 1 profiler per process.
  profiler = Profiler(sess.graph)

  for i in xrange(total_steps):
    if i % 10000 == 0:
      run_meta = tf.compat.v1.RunMetadata()
      _ = sess.run(...,
                   options=tf.compat.v1.RunOptions(
                       trace_level=tf.RunOptions.FULL_TRACE),
                   run_metadata=run_meta)
      profiler.add_step(i, run_meta)

      # Profile the parameters of your model.
      profiler.profile_name_scope(options=(option_builder.ProfileOptionBuilder
          .trainable_variables_parameter()))

      # Or profile the timing of your model operations.
      opts = option_builder.ProfileOptionBuilder.time_and_memory()
      profiler.profile_operations(options=opts)

      # Or you can generate a timeline:
      opts = (option_builder.ProfileOptionBuilder(
              option_builder.ProfileOptionBuilder.time_and_memory())
              .with_step(i)
              .with_timeline_output(filename).build())
      profiler.profile_graph(options=opts)
    else:
      _ = sess.run(...)
  # Auto detect problems and generate advice.
  profiler.advise()

 


 Args
  graph   tf.Graph. If None and eager execution is not enabled, use default graph.  
  op_log   optional. tensorflow::tfprof::OpLogProto proto. Used to define extra op types.    Methods add_step View source 
add_step(
    step, run_meta
)
 Add statistics of a step.
 


 Args
  step   int, An id used to group one or more different run_meta together. When profiling with the profile_xxx APIs, user can use the step id in the options to profile these run_meta together.  
  run_meta   RunMetadata proto that contains statistics of a session run.    advise View source 
advise(
    options
)
 Automatically detect problems and generate reports.
 


 Args
  options   A dict of options. See ALL_ADVICE example above.   
 


 Returns   An Advise proto that contains the reports from all checkers.  
 profile_graph View source 
profile_graph(
    options
)
 Profile the statistics of graph nodes, organized by dataflow graph.
 


 Args
  options   A dict of options. See core/profiler/g3doc/options.md.   
 


 Returns   a GraphNodeProto that records the results.  
 profile_name_scope View source 
profile_name_scope(
    options
)
 Profile the statistics of graph nodes, organized by name scope.
 


 Args
  options   A dict of options. See core/profiler/g3doc/options.md.   
 


 Returns   a GraphNodeProto that records the results.  
 profile_operations View source 
profile_operations(
    options
)
 Profile the statistics of the Operation types (e.g. MatMul, Conv2D).
 


 Args
  options   A dict of options. See core/profiler/g3doc/options.md.   
 


 Returns   a MultiGraphNodeProto that records the results.  
 profile_python View source 
profile_python(
    options
)
 Profile the statistics of the Python codes. By default, it shows the call stack from root. To avoid redundant output, you may use options to filter as below options['show_name_regexes'] = ['.my_code.py.']
 


 Args
  options   A dict of options. See core/profiler/g3doc/options.md.   
 


 Returns   a MultiGraphNodeProto that records the results.  
 serialize_to_string View source 
serialize_to_string()
 Serialize the ProfileProto to a binary string. Users can write it to file for offline analysis by tfprof commandline or graphical interface.
 


 Returns   ProfileProto binary string.