Support advisor in all places (Command line, APIs)

Add expensive operation checker

PiperOrigin-RevId: 160222348

4 files changed, 139 insertions, 29 deletions

diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/internal/pywrap_tensorflow_print_model_analysis.i b/tensorflow/contrib/tfprof/python/tools/tfprof/internal/pywrap_tensorflow_print_model_analysis.i
index 40f29ae8a2..582c36e339 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/internal/pywrap_tensorflow_print_model_analysis.i
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/internal/pywrap_tensorflow_print_model_analysis.i
@@ -43,7 +43,6 @@ using tensorflow::int64;
 %unignore tensorflow::tfprof::DeleteProfiler;
 %unignore tensorflow::tfprof::AddStep;
 %unignore tensorflow::tfprof::Profile;
-%unignore tensorflow::tfprof::Advise;
 
 %include "tensorflow/tools/tfprof/internal/print_model_analysis.h"
 
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py
index 419beac0b9..c781d2af4e 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py
@@ -20,6 +20,8 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import six
+
 from tensorflow.contrib.tfprof.python.tools.tfprof import tfprof_logger
 from tensorflow.contrib.tfprof.python.tools.tfprof.internal import pywrap_tensorflow_print_model_analysis_lib as print_mdl
 from tensorflow.python.framework import errors
@@ -108,49 +110,77 @@ PRINT_ALL_TIMING_MEMORY = {
     'dump_to_file': ''
 }
 
+# The following options are for 'advise' tfprof_cmd.
+# Show all advice.
+ALL_ADVICE = {
+    'ExpensiveOperationChecker': {},
+    'AcceleratorUtilizationChecker': {},
+    'JobChecker': {},  # Only available internally.
+    'OperationChecker': {},
+}
+
 # pylint: enable=bad-whitespace
 # pylint: enable=bad-continuation
 
 
-def _build_options(tfprof_options):
+def _build_options(options):
   """Build tfprof.OptionsProto.
 
   Args:
-    tfprof_options: A dictionary of options.
+    options: A dictionary of options.
   Returns:
     tfprof.OptionsProto.
   """
   opts = tfprof_options_pb2.OptionsProto()
-  opts.max_depth = tfprof_options.get('max_depth', 10)
-  opts.min_bytes = tfprof_options.get('min_bytes', 0)
-  opts.min_micros = tfprof_options.get('min_micros', 0)
-  opts.min_params = tfprof_options.get('min_params', 0)
-  opts.min_float_ops = tfprof_options.get('min_float_ops', 0)
-  opts.min_occurrence = tfprof_options.get('min_occurrence', 0)
+  opts.max_depth = options.get('max_depth', 10)
+  opts.min_bytes = options.get('min_bytes', 0)
+  opts.min_micros = options.get('min_micros', 0)
+  opts.min_params = options.get('min_params', 0)
+  opts.min_float_ops = options.get('min_float_ops', 0)
+  opts.min_occurrence = options.get('min_occurrence', 0)
 
-  opts.step = tfprof_options.get('step', -1)
+  opts.step = options.get('step', -1)
 
-  opts.order_by = tfprof_options.get('order_by', 'name')
+  opts.order_by = options.get('order_by', 'name')
 
-  for p in tfprof_options.get('account_type_regexes', []):
+  for p in options.get('account_type_regexes', []):
     opts.account_type_regexes.append(p)
-  for p in tfprof_options.get('start_name_regexes', []):
+  for p in options.get('start_name_regexes', []):
     opts.start_name_regexes.append(p)
-  for p in tfprof_options.get('trim_name_regexes', []):
+  for p in options.get('trim_name_regexes', []):
     opts.trim_name_regexes.append(p)
-  for p in tfprof_options.get('show_name_regexes', []):
+  for p in options.get('show_name_regexes', []):
     opts.show_name_regexes.append(p)
-  for p in tfprof_options.get('hide_name_regexes', []):
+  for p in options.get('hide_name_regexes', []):
     opts.hide_name_regexes.append(p)
-  opts.account_displayed_op_only = tfprof_options.get(
-      'account_displayed_op_only', False)
+  opts.account_displayed_op_only = options.get('account_displayed_op_only',
+                                               False)
 
-  for p in tfprof_options.get('select', []):
+  for p in options.get('select', []):
     opts.select.append(p)
 
-  opts.output = tfprof_options.get('output', 'stdout')
-  opts.dump_to_file = tfprof_options.get('dump_to_file', '')
+  opts.output = options.get('output', 'stdout')
+  opts.dump_to_file = options.get('dump_to_file', '')
+
+  return opts
+
+
+def _build_advisor_options(options):
+  """Build tfprof.AdvisorOptionsProto.
 
+  Args:
+    options: A dictionary of options. See ALL_ADVICE example.
+  Returns:
+    tfprof.AdvisorOptionsProto.
+  """
+  opts = tfprof_options_pb2.AdvisorOptionsProto()
+  if options is None:
+    return opts
+  for checker, checker_opts in six.iteritems(options):
+    checker_ops_pb = tfprof_options_pb2.AdvisorOptionsProto.CheckerOption()
+    for k, v in six.iteritems(checker_opts):
+      checker_ops_pb[k] = v
+    opts.checkers[checker].MergeFrom(checker_ops_pb)
   return opts
 
 
@@ -190,7 +220,7 @@ class Profiler(object):
       else:
         _ = sess.run(...)
     # Auto detect problems and generate advice.
-    profiler.advise()
+    profiler.advise(model_analyzer.ALL_ADVICE)
   """
 
   def __init__(self, graph, op_log=None):
@@ -288,9 +318,19 @@ class Profiler(object):
         print_mdl.Profile('graph'.encode('utf-8'), opts.SerializeToString()))
     return tfprof_node
 
-  def advise(self):
-    """Automatically detect problems and generate reports."""
-    print_mdl.Advise()
+  def advise(self, options=ALL_ADVICE):  # pylint: disable=dangerous-default-value
+    """Automatically detect problems and generate reports.
+
+    Args:
+      options: A dict of options.
+    Returns:
+      A Advise proto that conains the reports from all checkers.
+    """
+    advise_pb = tfprof_output_pb2.AdviceProto()
+    opts = _build_advisor_options(options)
+    advise_pb.ParseFromString(
+        print_mdl.Profile('advise'.encode('utf-8'), opts.SerializeToString()))
+    return advise_pb
 
 
 def print_model_analysis(graph,
@@ -354,3 +394,36 @@ def print_model_analysis(graph,
         None, None, 'unknown tfprof_cmd: %s\n' % tfprof_cmd)
 
   return tfprof_node
+
+
+def advise(graph, run_meta=None, tfprof_options=ALL_ADVICE):  # pylint: disable=dangerous-default-value
+  """Auto profile and advise.
+
+    Builds profiles and automatically check anormalies of various
+    aspects. See go/tfprof or README for examples and tutorials.
+
+  Args:
+    graph: tf.Graph.
+    run_meta: tensorflow::RunMetadata proto. Allows auto-profile
+              time and memroy.
+    tfprof_options: see ALL_ADVICE example above.
+  Returns:
+    Returns AdviceProto proto
+  """
+  # 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(tfprof_options)
+  ret = tfprof_output_pb2.AdviceProto()
+  ret.ParseFromString(
+      print_mdl.PrintModelAnalysis(
+          graph.as_graph_def(add_shapes=True).SerializeToString(),
+          run_meta_str,
+          op_log.SerializeToString(),
+          'advise'.encode('utf-8'),
+          opts.SerializeToString()))
+  return ret
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py
index 9db752c577..fea27a82a5 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py
@@ -126,7 +126,7 @@ class PrintModelAnalysisTest(test.TestCase):
     opts['account_displayed_op_only'] = False
     opts['select'] = ['params', 'float_ops']
 
-    with session.Session() as sess, ops.device('/cpu:0'):
+    with session.Session() as sess:
       x = lib.BuildFullModel()
 
       sess.run(variables.global_variables_initializer())
@@ -176,6 +176,7 @@ class PrintModelAnalysisTest(test.TestCase):
     opts['select'] = [
         'bytes', 'params', 'float_ops', 'device'
     ]
+    opts['output'] = 'none'
 
     with session.Session() as sess:
       x = lib.BuildSmallModel()
@@ -276,6 +277,33 @@ class PrintModelAnalysisTest(test.TestCase):
       self.assertEqual(total_children, 15)
       self.assertGreater(input_shapes, 0)
 
+  def testAdvisor(self):
+    ops.reset_default_graph()
+
+    with session.Session() as sess:
+      x = lib.BuildFullModel()
+
+      sess.run(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)
+
+      advice_pb = model_analyzer.advise(sess.graph, run_meta)
+      self.assertTrue('AcceleratorUtilizationChecker' in advice_pb.checkers)
+      self.assertTrue('ExpensiveOperationChecker' in advice_pb.checkers)
+      self.assertTrue('OperationChecker' in advice_pb.checkers)
+
+      checker = advice_pb.checkers['AcceleratorUtilizationChecker']
+      if test.is_gpu_available():
+        self.assertGreater(len(checker.reports), 0)
+      else:
+        self.assertEqual(len(checker.reports), 0)
+      checker = advice_pb.checkers['ExpensiveOperationChecker']
+      self.assertGreater(len(checker.reports), 0)
+
 
 if __name__ == '__main__':
   test.main()
diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/profiler_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/profiler_test.py
index 5daaafd7c8..c7113b6a57 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/profiler_test.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/profiler_test.py
@@ -129,7 +129,7 @@ class ProfilerTest(test.TestCase):
     opts = model_analyzer.PRINT_ALL_TIMING_MEMORY.copy()
     opts['account_type_regexes'] = ['.*']
 
-    with session.Session() as sess, ops.device('/cpu:0'):
+    with session.Session() as sess:
       r1, r2, r3 = lib.BuildSplitableModel()
       sess.run(variables.global_variables_initializer())
 
@@ -179,8 +179,18 @@ class ProfilerTest(test.TestCase):
       self.assertEqual(lib.SearchTFProfNode(pb2, 'add'), None)
       self.assertGreater(lib.SearchTFProfNode(pb3, 'add').exec_micros, 0)
 
-      # TODO(xpan): Better test of advisor.
-      profiler.advise()
+      advice_pb = profiler.advise(model_analyzer.ALL_ADVICE)
+      self.assertTrue('AcceleratorUtilizationChecker' in advice_pb.checkers)
+      self.assertTrue('ExpensiveOperationChecker' in advice_pb.checkers)
+      self.assertTrue('OperationChecker' in advice_pb.checkers)
+
+      checker = advice_pb.checkers['AcceleratorUtilizationChecker']
+      if test.is_gpu_available():
+        self.assertGreater(len(checker.reports), 0)
+      else:
+        self.assertEqual(len(checker.reports), 0)
+      checker = advice_pb.checkers['ExpensiveOperationChecker']
+      self.assertGreater(len(checker.reports), 0)
 
 
 if __name__ == '__main__':