Function advise

tensorflow/python/profiler/model_analyzer.py:385–420

Auto profile and advise. Builds profiles and automatically check anomalies of various aspects. For more details: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/README.md Args: graph: tf.Graph. If None and eager execution is not enabled, use

(graph=None, run_meta=None, options=_DEFAULT_ADVISE_OPTIONS)

@tf_export(v1=['profiler.advise'])
def advise(graph=None, run_meta=None, options=_DEFAULT_ADVISE_OPTIONS):
  """Auto profile and advise.

    Builds profiles and automatically check anomalies of various
    aspects. For more details:
    https://github.com/tensorflow/tensorflow/tree/master/tensorflow/core/profiler/README.md

  Args:
    graph: tf.Graph. If None and eager execution is not enabled, use
        default graph.
    run_meta: optional tensorflow.RunMetadata proto. It is necessary to
        to support run time information profiling, such as time and memory.
    options: see ALL_ADVICE example above. Default checks everything.
  Returns:
    Returns AdviceProto proto
  """
  if not graph and not context.executing_eagerly():
    graph = ops.get_default_graph()

  if options == _DEFAULT_ADVISE_OPTIONS:
    options = ALL_ADVICE.copy()

  # pylint: disable=protected-access
  op_log = tfprof_logger.merge_default_with_oplog(
      graph, None, run_meta, add_trace=True)
  # pylint: enable=protected-access

  run_meta_str = run_meta.SerializeToString() if run_meta else b''

  opts = _build_advisor_options(options)
  ret = tfprof_output_pb2.AdviceProto()
  ret.ParseFromString(
      print_mdl.PrintModelAnalysis(
          _graph_string(graph), run_meta_str, op_log.SerializeToString(),
          'advise'.encode('utf-8'), opts.SerializeToString()))
  return ret