Replace tf.flags usage with argparse everywhere

Change: 135688498

4 files changed, 160 insertions, 44 deletions

diff --git a/tensorflow/examples/how_tos/reading_data/convert_to_records.py b/tensorflow/examples/how_tos/reading_data/convert_to_records.py
index f52e5bdddd..66e1adec3e 100644
--- a/tensorflow/examples/how_tos/reading_data/convert_to_records.py
+++ b/tensorflow/examples/how_tos/reading_data/convert_to_records.py
@@ -18,10 +18,12 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 import os
+
 import tensorflow as tf
-from tensorflow.contrib.learn.python.learn.datasets import mnist
 
+from tensorflow.contrib.learn.python.learn.datasets import mnist
 
 SOURCE_URL = 'http://yann.lecun.com/exdb/mnist/'
 
@@ -31,13 +33,7 @@ TEST_IMAGES = 't10k-images-idx3-ubyte.gz'
 TEST_LABELS = 't10k-labels-idx1-ubyte.gz'
 
 
-tf.app.flags.DEFINE_string('directory', '/tmp/data',
-                           'Directory to download data files and write the '
-                           'converted result')
-tf.app.flags.DEFINE_integer('validation_size', 5000,
-                            'Number of examples to separate from the training '
-                            'data for the validation set.')
-FLAGS = tf.app.flags.FLAGS
+FLAGS = None
 
 
 def _int64_feature(value):
@@ -89,4 +85,22 @@ def main(argv):
 
 
 if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--directory',
+      type=str,
+      default='/tmp/data',
+      help='Directory to download data files and write the converted result'
+  )
+  parser.add_argument(
+      '--validation_size',
+      type=int,
+      default=5000,
+      help="""\
+      Number of examples to separate from the training data for the validation
+      set.\
+      """
+  )
+  FLAGS = parser.parse_args()
+
   tf.app.run()
diff --git a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py
index 9a33afd93a..d0482568a2 100644
--- a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py
+++ b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded.py
@@ -30,26 +30,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 import time
+
 import tensorflow as tf
 
 from tensorflow.examples.tutorials.mnist import input_data
 from tensorflow.examples.tutorials.mnist import mnist
 
-
 # Basic model parameters as external flags.
-flags = tf.app.flags
-FLAGS = flags.FLAGS
-flags.DEFINE_float('learning_rate', 0.01, 'Initial learning rate.')
-flags.DEFINE_integer('num_epochs', 2, 'Number of epochs to run trainer.')
-flags.DEFINE_integer('hidden1', 128, 'Number of units in hidden layer 1.')
-flags.DEFINE_integer('hidden2', 32, 'Number of units in hidden layer 2.')
-flags.DEFINE_integer('batch_size', 100, 'Batch size.  '
-                     'Must divide evenly into the dataset sizes.')
-flags.DEFINE_string('train_dir', '/tmp/data',
-                    'Directory to put the training data.')
-flags.DEFINE_boolean('fake_data', False, 'If true, uses fake data '
-                     'for unit testing.')
+FLAGS = None
 
 
 def run_training():
@@ -151,4 +141,49 @@ def main(_):
 
 
 if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--learning_rate',
+      type=float,
+      default=0.01,
+      help='Initial learning rate.'
+  )
+  parser.add_argument(
+      '--num_epochs',
+      type=int,
+      default=2,
+      help='Number of epochs to run trainer.'
+  )
+  parser.add_argument(
+      '--hidden1',
+      type=int,
+      default=128,
+      help='Number of units in hidden layer 1.'
+  )
+  parser.add_argument(
+      '--hidden2',
+      type=int,
+      default=32,
+      help='Number of units in hidden layer 2.'
+  )
+  parser.add_argument(
+      '--batch_size',
+      type=int,
+      default=100,
+      help='Batch size.  Must divide evenly into the dataset sizes.'
+  )
+  parser.add_argument(
+      '--train_dir',
+      type=str,
+      default='/tmp/data',
+      help='Directory to put the training data.'
+  )
+  parser.add_argument(
+      '--fake_data',
+      default=False,
+      help='If true, uses fake data for unit testing.',
+      action='store_true'
+  )
+  FLAGS = parser.parse_args()
+
   tf.app.run()
diff --git a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py
index b4c80e53b6..d037b8731c 100644
--- a/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py
+++ b/tensorflow/examples/how_tos/reading_data/fully_connected_preloaded_var.py
@@ -29,26 +29,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 import time
+
 import tensorflow as tf
 
 from tensorflow.examples.tutorials.mnist import input_data
 from tensorflow.examples.tutorials.mnist import mnist
 
-
 # Basic model parameters as external flags.
-flags = tf.app.flags
-FLAGS = flags.FLAGS
-flags.DEFINE_float('learning_rate', 0.01, 'Initial learning rate.')
-flags.DEFINE_integer('num_epochs', 2, 'Number of epochs to run trainer.')
-flags.DEFINE_integer('hidden1', 128, 'Number of units in hidden layer 1.')
-flags.DEFINE_integer('hidden2', 32, 'Number of units in hidden layer 2.')
-flags.DEFINE_integer('batch_size', 100, 'Batch size.  '
-                     'Must divide evenly into the dataset sizes.')
-flags.DEFINE_string('train_dir', '/tmp/data',
-                    'Directory to put the training data.')
-flags.DEFINE_boolean('fake_data', False, 'If true, uses fake data '
-                     'for unit testing.')
+FLAGS = None
 
 
 def run_training():
@@ -161,4 +151,49 @@ def main(_):
 
 
 if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--learning_rate',
+      type=float,
+      default=0.01,
+      help='Initial learning rate.'
+  )
+  parser.add_argument(
+      '--num_epochs',
+      type=int,
+      default=2,
+      help='Number of epochs to run trainer.'
+  )
+  parser.add_argument(
+      '--hidden1',
+      type=int,
+      default=128,
+      help='Number of units in hidden layer 1.'
+  )
+  parser.add_argument(
+      '--hidden2',
+      type=int,
+      default=32,
+      help='Number of units in hidden layer 2.'
+  )
+  parser.add_argument(
+      '--batch_size',
+      type=int,
+      default=100,
+      help='Batch size.  Must divide evenly into the dataset sizes.'
+  )
+  parser.add_argument(
+      '--train_dir',
+      type=str,
+      default='/tmp/data',
+      help='Directory to put the training data.'
+  )
+  parser.add_argument(
+      '--fake_data',
+      default=False,
+      help='If true, uses fake data for unit testing.',
+      action='store_true'
+  )
+  FLAGS = parser.parse_args()
+
   tf.app.run()
diff --git a/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py b/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py
index 351d531e25..127153a00b 100644
--- a/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py
+++ b/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py
@@ -27,23 +27,16 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 import os.path
 import time
+
 import tensorflow as tf
 
 from tensorflow.examples.tutorials.mnist import mnist
 
-
 # Basic model parameters as external flags.
-flags = tf.app.flags
-FLAGS = flags.FLAGS
-flags.DEFINE_float('learning_rate', 0.01, 'Initial learning rate.')
-flags.DEFINE_integer('num_epochs', 2, 'Number of epochs to run trainer.')
-flags.DEFINE_integer('hidden1', 128, 'Number of units in hidden layer 1.')
-flags.DEFINE_integer('hidden2', 32, 'Number of units in hidden layer 2.')
-flags.DEFINE_integer('batch_size', 100, 'Batch size.')
-flags.DEFINE_string('train_dir', '/tmp/data',
-                    'Directory with the training data.')
+FLAGS = None
 
 # Constants used for dealing with the files, matches convert_to_records.
 TRAIN_FILE = 'train.tfrecords'
@@ -194,4 +187,43 @@ def main(_):
 
 
 if __name__ == '__main__':
+  parser = argparse.ArgumentParser()
+  parser.add_argument(
+      '--learning_rate',
+      type=float,
+      default=0.01,
+      help='Initial learning rate.'
+  )
+  parser.add_argument(
+      '--num_epochs',
+      type=int,
+      default=2,
+      help='Number of epochs to run trainer.'
+  )
+  parser.add_argument(
+      '--hidden1',
+      type=int,
+      default=128,
+      help='Number of units in hidden layer 1.'
+  )
+  parser.add_argument(
+      '--hidden2',
+      type=int,
+      default=32,
+      help='Number of units in hidden layer 2.'
+  )
+  parser.add_argument(
+      '--batch_size',
+      type=int,
+      default=100,
+      help='Batch size.'
+  )
+  parser.add_argument(
+      '--train_dir',
+      type=str,
+      default='/tmp/data',
+      help='Directory with the training data.'
+  )
+  FLAGS = parser.parse_args()
+
   tf.app.run()