Merge pull request #2443 from tensorflow/flags

Flags

tutorials/image/cifar10/cifar10.py

@@ -35,6 +35,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 import os
 import re
 import sys
@@ -45,15 +46,19 @@ import tensorflow as tf
 
 import cifar10_input
 
-FLAGS = tf.app.flags.FLAGS
+parser = argparse.ArgumentParser()
 
 # Basic model parameters.
-tf.app.flags.DEFINE_integer('batch_size', 128,
-                            """Number of images to process in a batch.""")
-tf.app.flags.DEFINE_string('data_dir', '/tmp/cifar10_data',
-                           """Path to the CIFAR-10 data directory.""")
-tf.app.flags.DEFINE_boolean('use_fp16', False,
-                            """Train the model using fp16.""")
+parser.add_argument('--batch_size', type=int, default=128,
+                    help='Number of images to process in a batch.')
+
+parser.add_argument('--data_dir', type=str, default='/tmp/cifar10_data',
+                    help='Path to the CIFAR-10 data directory.')
+
+parser.add_argument('--use_fp16', type=bool, default=False,
+                    help='Train the model using fp16.')
+
+FLAGS = parser.parse_args()
 
 # Global constants describing the CIFAR-10 data set.
 IMAGE_SIZE = cifar10_input.IMAGE_SIZE

tutorials/image/cifar10/cifar10_eval.py

@@ -34,6 +34,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 from datetime import datetime
 import math
 import time
@@ -43,20 +44,25 @@ import tensorflow as tf
 
 import cifar10
 
-FLAGS = tf.app.flags.FLAGS
+parser = cifar10.parser
 
-tf.app.flags.DEFINE_string('eval_dir', '/tmp/cifar10_eval',
-                           """Directory where to write event logs.""")
-tf.app.flags.DEFINE_string('eval_data', 'test',
-                           """Either 'test' or 'train_eval'.""")
-tf.app.flags.DEFINE_string('checkpoint_dir', '/tmp/cifar10_train',
-                           """Directory where to read model checkpoints.""")
-tf.app.flags.DEFINE_integer('eval_interval_secs', 60 * 5,
-                            """How often to run the eval.""")
-tf.app.flags.DEFINE_integer('num_examples', 10000,
-                            """Number of examples to run.""")
-tf.app.flags.DEFINE_boolean('run_once', False,
-                         """Whether to run eval only once.""")
+parser.add_argument('--eval_dir', type=str, default='/tmp/cifar10_eval',
+                    help='Directory where to write event logs.')
+
+parser.add_argument('--eval_data', type=str, default='test',
+                    help='Either `test` or `train_eval`.')
+
+parser.add_argument('--checkpoint_dir', type=str, default='/tmp/cifar10_train',
+                    help='Directory where to read model checkpoints.')
+
+parser.add_argument('--eval_interval_secs', type=int, default=60*5,
+                    help='How often to run the eval.')
+
+parser.add_argument('--num_examples', type=int, default=10000,
+                    help='Number of examples to run.')
+
+parser.add_argument('--run_once', type=bool, default=False,
+                    help='Whether to run eval only once.')
 
 
 def eval_once(saver, summary_writer, top_k_op, summary_op):
@@ -154,4 +160,5 @@ def main(argv=None):  # pylint: disable=unused-argument
 
 
 if __name__ == '__main__':
+  FLAGS = parser.parse_args()
   tf.app.run()

tutorials/image/cifar10/cifar10_multi_gpu_train.py

@@ -39,6 +39,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 from datetime import datetime
 import os.path
 import re
@@ -49,17 +50,19 @@ from six.moves import xrange  # pylint: disable=redefined-builtin
 import tensorflow as tf
 import cifar10
 
-FLAGS = tf.app.flags.FLAGS
+parser = cifar10.parser
 
-tf.app.flags.DEFINE_string('train_dir', '/tmp/cifar10_train',
-                           """Directory where to write event logs """
-                           """and checkpoint.""")
-tf.app.flags.DEFINE_integer('max_steps', 1000000,
-                            """Number of batches to run.""")
-tf.app.flags.DEFINE_integer('num_gpus', 1,
-                            """How many GPUs to use.""")
-tf.app.flags.DEFINE_boolean('log_device_placement', False,
-                            """Whether to log device placement.""")
+parser.add_argument('--train_dir', type=str, default='/tmp/cifar10_train',
+                    help='Directory where to write event logs and checkpoint.')
+
+parser.add_argument('--max_steps', type=int, default=1000000,
+                    help='Number of batches to run.')
+
+parser.add_argument('--num_gpus', type=int, default=1,
+                    help='How many GPUs to use.')
+
+parser.add_argument('--log_device_placement', type=bool, default=False,
+                    help='Whether to log device placement.')
 
 
 def tower_loss(scope, images, labels):
@@ -274,4 +277,5 @@ def main(argv=None):  # pylint: disable=unused-argument
 
 
 if __name__ == '__main__':
+  FLAGS = parser.parse_args()
   tf.app.run()

tutorials/image/cifar10/cifar10_train.py

@@ -36,6 +36,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import argparse
 from datetime import datetime
 import time
 
@@ -43,17 +44,19 @@ import tensorflow as tf
 
 import cifar10
 
-FLAGS = tf.app.flags.FLAGS
+parser = cifar10.parser
 
-tf.app.flags.DEFINE_string('train_dir', '/tmp/cifar10_train',
-                           """Directory where to write event logs """
-                           """and checkpoint.""")
-tf.app.flags.DEFINE_integer('max_steps', 1000000,
-                            """Number of batches to run.""")
-tf.app.flags.DEFINE_boolean('log_device_placement', False,
-                            """Whether to log device placement.""")
-tf.app.flags.DEFINE_integer('log_frequency', 10,
-                            """How often to log results to the console.""")
+parser.add_argument('--train_dir', type=str, default='/tmp/cifar10_train',
+                    help='Directory where to write event logs and checkpoint.')
+
+parser.add_argument('--max_steps', type=int, default=1000000,
+                    help='Number of batches to run.')
+
+parser.add_argument('--log_device_placement', type=bool, default=False,
+                    help='Whether to log device placement.')
+
+parser.add_argument('--log_frequency', type=int, default=10,
+                    help='How often to log results to the console.')
 
 
 def train():
@@ -124,4 +127,5 @@ def main(argv=None):  # pylint: disable=unused-argument
 
 
 if __name__ == '__main__':
+  FLAGS = parser.parse_args()
   tf.app.run()