Automated g4 rollback of changelist 159897279

PiperOrigin-RevId: 160198598

4 files changed, 29 insertions, 139 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 582c36e339..40f29ae8a2 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
@@ -43,6 +43,7 @@ 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 c781d2af4e..419beac0b9 100644
--- a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py
+++ b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py
@@ -20,8 +20,6 @@ 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
@@ -110,77 +108,49 @@ 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(options):
+def _build_options(tfprof_options):
   """Build tfprof.OptionsProto.
 
   Args:
-    options: A dictionary of options.
+    tfprof_options: A dictionary of options.
   Returns:
     tfprof.OptionsProto.
   """
   opts = tfprof_options_pb2.OptionsProto()
-  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.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.step = options.get('step', -1)
+  opts.step = tfprof_options.get('step', -1)
 
-  opts.order_by = options.get('order_by', 'name')
+  opts.order_by = tfprof_options.get('order_by', 'name')
 
-  for p in options.get('account_type_regexes', []):
+  for p in tfprof_options.get('account_type_regexes', []):
     opts.account_type_regexes.append(p)
-  for p in options.get('start_name_regexes', []):
+  for p in tfprof_options.get('start_name_regexes', []):
     opts.start_name_regexes.append(p)
-  for p in options.get('trim_name_regexes', []):
+  for p in tfprof_options.get('trim_name_regexes', []):
     opts.trim_name_regexes.append(p)
-  for p in options.get('show_name_regexes', []):
+  for p in tfprof_options.get('show_name_regexes', []):
     opts.show_name_regexes.append(p)
-  for p in options.get('hide_name_regexes', []):
+  for p in tfprof_options.get('hide_name_regexes', []):
     opts.hide_name_regexes.append(p)
-  opts.account_displayed_op_only = options.get('account_displayed_op_only',
-                                               False)
+  opts.account_displayed_op_only = tfprof_options.get(
+      'account_displayed_op_only', False)
 
-  for p in options.get('select', []):
+  for p in tfprof_options.get('select', []):
     opts.select.append(p)
 
-  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.
+  opts.output = tfprof_options.get('output', 'stdout')
+  opts.dump_to_file = tfprof_options.get('dump_to_file', '')
 
-  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
 
 
@@ -220,7 +190,7 @@ class Profiler(object):
       else:
         _ = sess.run(...)
     # Auto detect problems and generate advice.
-    profiler.advise(model_analyzer.ALL_ADVICE)
+    profiler.advise()
   """
 
   def __init__(self, graph, op_log=None):
@@ -318,19 +288,9 @@ class Profiler(object):
         print_mdl.Profile('graph'.encode('utf-8'), opts.SerializeToString()))
     return tfprof_node
 
-  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 advise(self):
+    """Automatically detect problems and generate reports."""
+    print_mdl.Advise()
 
 
 def print_model_analysis(graph,
@@ -394,36 +354,3 @@ 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 fea27a82a5..9db752c577 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:
+    with session.Session() as sess, ops.device('/cpu:0'):
       x = lib.BuildFullModel()
 
       sess.run(variables.global_variables_initializer())
@@ -176,7 +176,6 @@ class PrintModelAnalysisTest(test.TestCase):
     opts['select'] = [
         'bytes', 'params', 'float_ops', 'device'
     ]
-    opts['output'] = 'none'
 
     with session.Session() as sess:
       x = lib.BuildSmallModel()
@@ -277,33 +276,6 @@ 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 c7113b6a57..5daaafd7c8 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:
+    with session.Session() as sess, ops.device('/cpu:0'):
       r1, r2, r3 = lib.BuildSplitableModel()
       sess.run(variables.global_variables_initializer())
 
@@ -179,18 +179,8 @@ class ProfilerTest(test.TestCase):
       self.assertEqual(lib.SearchTFProfNode(pb2, 'add'), None)
       self.assertGreater(lib.SearchTFProfNode(pb3, 'add').exec_micros, 0)
 
-      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)
+      # TODO(xpan): Better test of advisor.
+      profiler.advise()
 
 
 if __name__ == '__main__':