Merge remote-tracking branch 'upstream/master'

CODEOWNERS

@@ -10,7 +10,7 @@
 /research/compression/ @nmjohn
 /research/deeplab/ @aquariusjay @yknzhu @gpapan
 /research/delf/ @andrefaraujo
-/research/differential_privacy/ @panyx0718
+/research/differential_privacy/ @panyx0718 @mironov
 /research/domain_adaptation/ @bousmalis @dmrd
 /research/gan/ @joel-shor
 /research/im2txt/ @cshallue

official/mnist/mnist.py

@@ -24,7 +24,7 @@ import tensorflow as tf  # pylint: disable=g-bad-import-order
 
 from official.mnist import dataset
 from official.utils.arg_parsers import parsers
-from official.utils.logging import hooks_helper
+from official.utils.logs import hooks_helper
 
 LEARNING_RATE = 1e-4
 

official/mnist/mnist_eager.py

@@ -107,7 +107,7 @@ def main(argv):
     (device, data_format) = ('/cpu:0', 'channels_last')
   # If data_format is defined in FLAGS, overwrite automatically set value.
   if flags.data_format is not None:
-    data_format = data_format
+    data_format = flags.data_format
   print('Using device %s, and data format %s.' % (device, data_format))
 
   # Load the datasets

official/resnet/resnet_run_loop.py

@@ -31,8 +31,8 @@ import tensorflow as tf  # pylint: disable=g-bad-import-order
 from official.resnet import resnet_model
 from official.utils.arg_parsers import parsers
 from official.utils.export import export
-from official.utils.logging import hooks_helper
-from official.utils.logging import logger
+from official.utils.logs import hooks_helper
+from official.utils.logs import logger
 
 
 ################################################################################

official/utils/arg_parsers/parsers.py

@@ -132,7 +132,7 @@ class BaseParser(argparse.ArgumentParser):
                "Example: --hooks LoggingTensorHook ExamplesPerSecondHook. "
                "Allowed hook names (case-insensitive): LoggingTensorHook, "
                "ProfilerHook, ExamplesPerSecondHook, LoggingMetricHook."
-               "See official.utils.logging.hooks_helper for details.",
+               "See official.utils.logs.hooks_helper for details.",
           metavar="<HK>"
       )
 

official/utils/logging/benchmark_uploader.py → official/utils/logs/benchmark_uploader.py

@@ -34,7 +34,7 @@ from google.cloud import bigquery
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
 from official.utils.arg_parsers import parsers
-from official.utils.logging import logger
+from official.utils.logs import logger
 
 
 class BigQueryUploader(object):

official/utils/logging/hooks_helper.py → official/utils/logs/hooks_helper.py

@@ -26,8 +26,8 @@ from __future__ import print_function
 
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
-from official.utils.logging import hooks
-from official.utils.logging import metric_hook
+from official.utils.logs import hooks
+from official.utils.logs import metric_hook
 
 _TENSORS_TO_LOG = dict((x, x) for x in ['learning_rate',
                                         'cross_entropy',

official/utils/logging/hooks_helper_test.py → official/utils/logs/hooks_helper_test.py

@@ -23,7 +23,7 @@ import unittest
 
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
-from official.utils.logging import hooks_helper
+from official.utils.logs import hooks_helper
 
 
 class BaseTest(unittest.TestCase):

official/utils/logging/hooks_test.py → official/utils/logs/hooks_test.py

@@ -24,7 +24,7 @@ import time
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 from tensorflow.python.training import monitored_session  # pylint: disable=g-bad-import-order
 
-from official.utils.logging import hooks
+from official.utils.logs import hooks
 
 
 tf.logging.set_verbosity(tf.logging.ERROR)

official/utils/logging/logger_test.py → official/utils/logs/logger_test.py

@@ -26,7 +26,7 @@ import unittest
 
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
-from official.utils.logging import logger
+from official.utils.logs import logger
 
 
 class BenchmarkLoggerTest(tf.test.TestCase):

official/utils/logging/metric_hook.py → official/utils/logs/metric_hook.py

@@ -18,9 +18,9 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import tensorflow as tf
+import tensorflow as tf  # pylint: disable=g-bad-import-order
 
-from official.utils.logging import logger
+from official.utils.logs import logger
 
 
 class LoggingMetricHook(tf.train.LoggingTensorHook):

official/utils/logging/metric_hook_test.py → official/utils/logs/metric_hook_test.py

@@ -24,15 +24,17 @@ import time
 import tensorflow as tf
 from tensorflow.python.training import monitored_session
 
-from official.utils.logging import metric_hook
+from official.utils.logs import metric_hook  # pylint: disable=g-bad-import-order
 
 
 class LoggingMetricHookTest(tf.test.TestCase):
+  """Tests for LoggingMetricHook."""
 
   def setUp(self):
     super(LoggingMetricHookTest, self).setUp()
 
     class MockMetricLogger(object):
+
       def __init__(self):
         self.logged_metric = []
 

official/wide_deep/wide_deep.py

@@ -25,7 +25,7 @@ import sys
 import tensorflow as tf  # pylint: disable=g-bad-import-order
 
 from official.utils.arg_parsers import parsers
-from official.utils.logging import hooks_helper
+from official.utils.logs import hooks_helper
 
 _CSV_COLUMNS = [
     'age', 'workclass', 'fnlwgt', 'education', 'education_num',

research/README.md

@@ -28,8 +28,8 @@ installation](https://www.tensorflow.org/install).
     pre-trained Residual GRU network.
 -   [deeplab](deeplab): deep labelling for semantic image segmentation.
 -   [delf](delf): deep local features for image matching and retrieval.
--   [differential_privacy](differential_privacy): privacy-preserving student
-    models from multiple teachers.
+-   [differential_privacy](differential_privacy): differential privacy for training
+    data.
 -   [domain_adaptation](domain_adaptation): domain separation networks.
 -   [gan](gan): generative adversarial networks.
 -   [im2txt](im2txt): image-to-text neural network for image captioning.

research/attention_ocr/python/common_flags.py

@@ -73,7 +73,7 @@ def define():
   flags.DEFINE_string('optimizer', 'momentum',
                       'the optimizer to use')
 
-  flags.DEFINE_string('momentum', 0.9,
+  flags.DEFINE_float('momentum', 0.9,
                       'momentum value for the momentum optimizer if used')
 
   flags.DEFINE_bool('use_augment_input', True,

research/deeplab/common.py

@@ -95,7 +95,6 @@ ORIGINAL_IMAGE = 'original_image'
 # Test set name.
 TEST_SET = 'test'
 
-
 class ModelOptions(
     collections.namedtuple('ModelOptions', [
         'outputs_to_num_classes',

research/deeplab/core/xception_test.py

@@ -14,6 +14,7 @@
 # ==============================================================================
 
 """Tests for xception.py."""
+import six
 import numpy as np
 import tensorflow as tf
 
@@ -309,7 +310,7 @@ class XceptionNetworkTest(tf.test.TestCase):
           'xception/middle_flow/block1': [2, 14, 14, 4],
           'xception/exit_flow/block1': [2, 7, 7, 8],
           'xception/exit_flow/block2': [2, 7, 7, 16]}
-      for endpoint, shape in endpoint_to_shape.iteritems():
+      for endpoint, shape in six.iteritems(endpoint_to_shape):
         self.assertListEqual(end_points[endpoint].get_shape().as_list(), shape)
 
   def testFullyConvolutionalEndpointShapes(self):
@@ -330,7 +331,7 @@ class XceptionNetworkTest(tf.test.TestCase):
           'xception/middle_flow/block1': [2, 21, 21, 4],
           'xception/exit_flow/block1': [2, 11, 11, 8],
           'xception/exit_flow/block2': [2, 11, 11, 16]}
-      for endpoint, shape in endpoint_to_shape.iteritems():
+      for endpoint, shape in six.iteritems(endpoint_to_shape):
         self.assertListEqual(end_points[endpoint].get_shape().as_list(), shape)
 
   def testAtrousFullyConvolutionalEndpointShapes(self):
@@ -352,7 +353,7 @@ class XceptionNetworkTest(tf.test.TestCase):
           'xception/middle_flow/block1': [2, 41, 41, 4],
           'xception/exit_flow/block1': [2, 41, 41, 8],
           'xception/exit_flow/block2': [2, 41, 41, 16]}
-      for endpoint, shape in endpoint_to_shape.iteritems():
+      for endpoint, shape in six.iteritems(endpoint_to_shape):
         self.assertListEqual(end_points[endpoint].get_shape().as_list(), shape)
 
   def testAtrousFullyConvolutionalValues(self):